k-Nearest Neighbors & Chatbots 2019


Notes:

The k-nearest neighbors algorithm is a non-parametric statistical method for classification and regression. k-Nearest Neighbors is often spelled “k-Nearest Neighbor” (without “s”), and k-NN or kNN for short.

Wikipedia:

References:

See also:

100 Best k-Nearest Neighbors VideosArtificial Imagination | Humor Generation 2018 | Stanford NLP & Dialog Systems | Text Segmentation 2018


Chatbot for Disease Prediction and Treatment Recommendation using Machine Learning
RB Mathew, S Varghese, SE Joy… – 2019 3rd International …, 2019 – ieeexplore.ieee.org
… From sklearn.neighbors import KNeighborsClassifier (1) def create_model(): neigh = KNeighborsClassifier(n_neighbors … [9] R. Ranoliya, N. Raghuwanshi, S. Singh, “Chatbot for university … Gupta , Kratika Goyal , Dharna Gureja, “An Enhanced K-Nearest Neighbor Algorithm …

Efficient task-specific data valuation for nearest neighbor algorithms
R Jia, D Dao, B Wang, FA Hubis, NM Gurel, B Li… – arXiv preprint arXiv …, 2019 – arxiv.org
… One example is that complex ML tasks such as chatbot training often relies on massive … Depending on whether the nearest neighbor algorithm is used for classification or regression, Y is … feature and assigning a label to the query according to the labels of its K nearest neighbors …

K-Nearest neighbor algorithm on implicit feedback to determine SOP
MYH Setyawan, RM Awangga, NA Lestari – Telkomnika, 2019 – researchgate.net
… Comparison of Multinomial Naive Bayes Algorithm And Logistic Regression For Intent Classification In Chatbot … Blknn: A k-nearest neighbors method for predicting bioluminescent proteins … Student performance prediction using support vector machine and k-nearest neighbor …

Focused domain contextual AI chatbot framework for resource poor languages
A Paul, A Haque Latif, F Amin Adnan… – Journal of Information …, 2019 – Taylor & Francis
… Method 2: centroid K nearest neighbour (CenKNN) … 1 ? dist ( x t , x i ) ) ? I ( x i , Ta g j ) Here KNN xt indicates the set of K nearest neighbours of x … For building the chatbot architecture we focused and tested several variation of Feed Forward Neural Network instead of a Feedback …

A Virtual Confucius Chatbot
AD Cheok, EY Zhang – Human–Robot Intimate Relationships, 2019 – Springer
… Block diagram of the virtual Confucius chatbot system … To improve the retrieval accuracy of the system, we have employed k-nearest neighbours algorithm (k-NN) to classify the database entries … The k-nearest neighbour algorithm is simple and widely used in text classification [14 …

Natural Language Processing and chat-bot implementation
P Eyno – 2019 – theseus.fi
… 3.2.5 KNeighbors “In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non … assigned to the class most common among its k nearest neighbours (k is a positive integer, typically small) … simply assigned to the class of that single nearest neighbour …

Diabot: A Predictive Medical Chatbot using Ensemble Learning
M Bali, S Mohanty, S Chatterjee, M Sarma… – academia.edu
… Chatbots have seen an unprecedented growth over the years as shown in Fig 1 and … Therefore, in this work we present a NLU-based chatbot which engages with the … six classifiers – Naïve Bayes (NB), Decision tree (DT), Random forest(RF), K-nearest neighbour(KNN), Logistic …

Disease Prognosis with Symptoms Endorsement using Combinational Classifier
M Giri, R Ganorkar, G Suki, S Deshpande, A Deshmukh – ijfrcsce.org
… pre- specified knowledge base(KB).Symptoms identified using association rules are used for making predictions.K-nearest neighbor algorithm finds … Now select all k neighbors and insert into set of K={D1,D2,D3,….Dk} I = K … k-nearest neighbour, decision tree and naive bayes …

Recognition and Prediction of Breast Cancer using Supervised Diagnosis
V Chaitanya, SM Killedar, D Revankar… – … on Recent Trends …, 2019 – ieeexplore.ieee.org
… involves comparison of the pixel in the input image with its neighbors to generate the … The k-nearest neighbours (KNN) algorithm is another supervised machine learning algorithm used to solve both … The Chatbot is first trained by integrating it with Artificial Intelligence using Java …

Machine learning techniques to reduce error in the internet of things
A Bhatnagar, S Shukla… – 2019 9th International …, 2019 – ieeexplore.ieee.org
… In classification it is used to classify the object into the most common class among its k- nearest neighbors … This can be achieved by implementing K nearest neighbor machine … Neighborhood selection strategy was then used to remove drawbacks of PSO [26] …

Characterizing and detecting livestreaming chatbots
S Jain, D Niranjan, H Lamba, N Shah… – Proceedings of the 2019 …, 2019 – dl.acm.org
… Upon obtaining the seed sets Rcb and Rr, we constructed a k-nearest-neighbors (kNN) graph between all … IMDs are used to infer in a supervised fashion if user is a chatbot or not … that operates on user groups; hence, we apply it for each stream to identify constitutent chatbots …

Social Relation Extraction from Chatbot Conversations: A Shortest Dependency Path Approach
M Glas – SKILL 2019-Studierendenkonferenz Informatik, 2019 – dl.gi.de
… S-REX, a comparison method for extracting social relations from chatbot conversations … language conversations, used within chat messages between people, or humans and chatbots … Machine (SVM), Perceptron Algorithm Uneven Margin (PAUN) and K-Nearest-Neighbour (KNN …

AgriBot-An intelligent interactive interface to assist farmers in agricultural activities
D Sawant, A Jaiswal, J Singh… – 2019 IEEE Bombay …, 2019 – ieeexplore.ieee.org
… There can be an option of choosing local language to communicate with the chatbot in speech format would make app very feasible for use even to the farmers having very low exposure … A. K-nearest neighbor algorithm 1) Working of KNN algorithm: K Nearest Neighbors is a …

A quick review of machine learning algorithms
S Ray – 2019 International conference on machine learning …, 2019 – ieeexplore.ieee.org
… For example, the price of a house depends on many factors like the neighborhood it is situated in … K Nearest Neighbor (KNN) Algorithm is a classification algorithm It uses a database which is having data points grouped … It requires distance computation of k-nearest neighbors …

Text Emotion Distribution Learning from Small Sample: A Meta-Learning Approach
Z Zhao, X Ma – Proceedings of the 2019 Conference on Empirical …, 2019 – aclweb.org
… emotions in text automatically is an im- portant topic (Yadollahi et al., 2017) with widely used applications such as classifying e-commerce products reviews (Rao et al., 2016) and devel- oping emotionally intelligent chatbots for health … s K-nearest neighbors neighbor search …

Conversational Chatbot System For Student Support In Administrative Exam Information
HA Rasheed, J Zenkert, C Weber, M Fathi – researchgate.net
… In order to analyze the input sentence from the user, chatbots utilize methods of Natural Language Processing (NLP) … A comprehensive Chatbot … Traditional text classification methods include naïve Bayes, support vector machine (SVM), and k- nearest neighbour …

Automatic emotion-based music classification for supporting intelligent IoT applications
YS Seo, JH Huh – Electronics, 2019 – mdpi.com
… analysis is performed with different classification algorithms, such as random forest, deep neural network and K-nearest neighbor, as well as … acoustic features of music, many studies used different classifier to recognize music emotion, such as K-nearest neighbors [33], support …

Remote cardiovascular health monitoring system with auto-diagnosis
B Bhattacharya, S Mohapatra… – … on Vision Towards …, 2019 – ieeexplore.ieee.org
… Figure 5. Chatbot Questionnaire … D.6. Fuzzy K-Nearest Neighbor (FKNN) The main improvement of using the FKNN over KNN is that despite its deterministic form … In this case, closer neighbors of a query point will have a greater influence than neighbors which are further away …

Subword semantic hashing for intent classification on small datasets
K Shridhar, A Dash, A Sahu… – … Joint Conference on …, 2019 – ieeexplore.ieee.org
… is the intent classi- fication for industries like CRMs, Chatbots, business process … out with a number of classifiers, namely Ridge Classifier, K-Nearest Neighbors (KNN) Classifier … OF DIFFERENT NLU SERVICES WITH OUR APPROACH Platform Chatbot AskUbuntu WebApp …

An Applicative Study of Advances in Machine Learning
S Goel, I Khan, T Garg – 2019 6th International Conference on …, 2019 – ieeexplore.ieee.org
… Linear Regression > Clustering > Artificial Neural Network(ANN) > Support Vector Machines > Random Forest > Decision Tree > K-Nearest Neighbors … node speaks to the specific estimation of an objective variable [13] also, K nearest neighbours is a … K-Nearest Neighbor 78 …

Pun Detection using Soft Computing Techniques
A Jaiswal – … Conference on Machine Learning, Big Data …, 2019 – ieeexplore.ieee.org
… Chat-bots and Speech-Text based assistants are becoming increasingly popular … Decision Tree 0.7324 0.8285 0.6398 Naïve Bayes 0.7565 0.8419 0.6862 K-Nearest Neighbours 0.5778 0.7515 … K- Nearest Neighbors did not do quite well for the dataset, however, this must only …

Relevance Proximity Graphs for Fast Relevance Retrieval
S Morozov, A Babenko – arXiv preprint arXiv:1908.06887, 2019 – arxiv.org
… of a wide range of machine learning applications, eg, recommender services, retrieval-based chatbot systems, web … vj are connected by an edge if vj belongs to the set of k nearest neighbors of vi in … and then on each step moves from the current vertex to a neighbor, that appears …

Intelligent Collection and Analysis of Citizens’ Reports.
G Angiani, P Fornacciari, G Lombardo, M Mordonini… – WOA, 2019 – ceur-ws.org
… possible to create distributed applications for the administration of cities and neighborhood, using data … Infact, one of the most adavanced e-Government chatbot, the Burgeramter chatbot [12], provided … Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN …

Estimation Method of L2 Learners’ Second Language Ability by using Features in Conversation
X Chen, MHURR Khan, K Wakabayashi – Proceedings of the 21st …, 2019 – dl.acm.org
… The goal of Unriza and Carolina’s master thesis [18] was to make a chatbot with user having a … the feature value of the k-nearest neighbor regression algo- rithm with T = 600, ? = 0.27 … Feature Pattern Linear K-Neighbors Baseline 104.61 S(3) 116.13 118.48 T = 200 , ? = 0.40 S …

Machine learning with R: expert techniques for predictive modeling
B Lantz – 2019 – books.google.com
… relationships between variables 60 Visualizing relationships – scatterplots 60 Examining relationships – two-way cross-tabulations 62 Summary 64 Chapter 3 – Lazy Learning – Classification Using Nearest Neighbors 65 Understanding nearest neighbor classification 66 …

Enabling a Bot with Understanding Argumentation and Providing Arguments
B Galitsky – Developing Enterprise Chatbots, 2019 – Springer
… The purpose of argumentation analysis for chatbots is twofold … 1. Nearest Neighbor (kNN) learning with explicit engineering of graph descriptions … chats in a domain such as politics, where it is important to select an answer tailored to a user political views, the chatbot needs to …

Intelligent Tourist System
IU Haque, M Rhaman – 2019 – dspace.daffodilvarsity.edu.bd
Page 1. INTELLIGENT TOURIST SYSTEM BY INJAMAM-UL- HAQUE ID: 152-15-445 & MD. ASIF RHAMAN ID: 151-15-341 This Report Presented in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Computer Science and Engineering …

Ishop: A voice Enabled Erp System for Searching Products
M Anik, M Hasan – 2019 – dspace.daffodilvarsity.edu.bd
Page 1. INTELLIGENT TOURIST SYSTEM BY INJAMAM-UL- HAQUE ID: 152-15-445 & MD. ASIF RHAMAN ID: 151-15-341 This Report Presented in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Computer Science and Engineering …

Machine Learning Tools for Probability of Default and Rating Downgrades of Corporate and Government Bonds
J Choudary, J Osterrieder – Available at SSRN 3461558, 2019 – papers.ssrn.com
… The field of ap- plications is wide-ranging eg process automation (chat- bots, paperwork automation), security (fraud … k-nearest neighbor is based on the idea of similarity what means that similar data points lie … k stands for the number of neighbors that vote to which class this new …

Real-World Application of Machine Learning and Deep Learning
SR Sree, SB Vyshnavi… – … Conference on Smart …, 2019 – ieeexplore.ieee.org
… Robots, chatbots are all developed on machine learning which tend to acquire this lifelong machine learning by interacting with humans and their daily systems [11] … K-Nearest Neighbor Method Steps: Input training data set, value ‘k’ (number of nearest neighbors to be …

A Comparative Study of Machine Learning Techniques in Healthcare
D Jain, B Kadecha, S Iyer – 2019 6th International Conference …, 2019 – ieeexplore.ieee.org
… 1. Babylon Health?s chatbot app [10] … Following are the main classification algorithms used in healthcare: 1) K-Nearest Neighbour (K-NN) K-NN is a non-parametric method used for classification, prediction of test data is done on the basis of its neighbour using voting system …

Machine Learning Algorithms
N Dhanda, SS Datta, M Dhanda – Computational Intelligence in the …, 2019 – igi-global.com
… K NEAREST NEIGHBOR ALGORITHM K nearest Neighbor Algorithm (KNN) is a classification algorithm … Page 13. 222 Machine Learning Algorithms Distances evaluated are then ranked and 3 nearest neighbor are determined. We collect the classes of these nearest neighbors …

Assistive System in Conversational Agent for Health Coaching: The CoachAI Approach
A Fadhil – arXiv preprint arXiv:1904.11412, 2019 – arxiv.org
… Chatbots offer simplicity, adaptiveness, constant presence and motivation to patient’s while interacting … 3; 14 end 15 foreach pi 2 P do 16 KNN; (K nearest neighbours); 17 end … of the patient’s spending time on their messaging apps makes using a chatbot application extremely …

Power System Transient Stability Prediction Algorithm Based on ReliefF and LSTM
B Li, T Wen, C Hu, B Zhou – International Conference on Artificial …, 2019 – Springer
… classes of each R. In the sample set, find k neighbor samples (near … document summarization, speech recognition image recognition, handwriting recognition, control of chat bots, predictive disease … the N labeled sample data, after that, we can find the k nearest neighbors H j (j …

MSc in Computer Science
RB Sulaiman – researchgate.net
… CHAPTER INFORMATION IN THIS CHAPTER ? Overview ? Chatbot system ? Chatbot technology ? Types of chatbot ? Comparison of chatbots ? Functions of chatbot ? Syntactic analysis ? Vector space model ? Machine learning models ? Support vector machines (SVM) …

Complicated table structure recognition
Z Chi, H Huang, HD Xu, H Yu, W Yin… – arXiv preprint arXiv …, 2019 – arxiv.org
… In this paper, we use a simple K nearest neighbors (KNN) method to construct E , in which each vertex is connected to its K nearest neighbors so that the total number of edges will be reduced to O(K|V |). In the next sub-section, we will introduce GraphTSR, which takes …

Intention and Engagement Recognition for Personalized Human-Robot Interaction, an integrated and Deep Learning approach
SP Pattar, E Coronado, LR Ardila… – 2019 IEEE 4th …, 2019 – ieeexplore.ieee.org
… In our work, we have used of One-Shot Detection algorithm and K Nearest Neighbours (KNN) … Chatbot Integration: In order to understand the general meaning of the sentences of the users we use a Natural Processing Language tool that enables the development of advanced …

Application of machine learning models for survival prognosis in breast cancer studies
I Mihaylov, M Nisheva, D Vassilev – Information, 2019 – mdpi.com
… Machine-Regression (SVR) with different kernels: RBF, Linear, and Polynomial, as well as Lasso regression, Kernel Ridge regression, K-neighborhood regression, decision … K-neighbors regressor—a supervised learning method based on k-nearest neighbor, which is a …

Learning from noisy data through robust feature selection, ensembles and simulation-based optimization
A Mariello – 2019 – eprints-phd.biblio.unitn.it
… Feature Selection Based on the Neighbor- hood Entropy … Abstract: In this work we propose a new measure for feature selection that is related to Mutual Information, called Neighborhood Entropy … volving approximated nearest-neighbors and locality-sensitive hashing …

Hands-On Machine Learning with IBM Watson: Leverage IBM Watson to implement machine learning techniques and algorithms using Python
JD Miller – 2019 – books.google.com
… 112 Try it out 118 Data cleansing and preparation K-means clustering using Python The Python code 120 121 121 Observing the results 123 Implementing in Watson 123 Saving your work K-nearest neighbors 126 126 … You will learn how to build chatbots using NLP techniques …

Training Set Expansion Using Word Embeddings for Korean Medical Information Extraction
YM Kim – … Data Management, Polystores, and Analytics for …, 2019 – Springer
… The candidate words for each entity type are found by searching k-nearest neighbors of each auto … With this manual verification, we can expand the number of neighbors to verify that … is partially supported by two projects, Smart Multimodal Environment of AI Chatbot Robots for …

Symptom Based Health Prediction using Data Mining
SV Shetty, GA Karthik, M Ashwin – … International Conference on …, 2019 – ieeexplore.ieee.org
… The experiment revealed K-Nearest Neighbour is susceptible to noisy data … Figure 5: T-stochastic neighbor … 1-7. [11] N. Albayrak, A. Özdemir and E. Zeydan, “An overview of artificial intelligence based chatbots and an example chatbot application,” 2018 26th Signal Processing …

Corporate IT-support Help-Desk Process Hybrid-Automation Solution with Machine Learning Approach
K Shanmugalingam, N Chandrasekara… – 2019 Digital Image …, 2019 – ieeexplore.ieee.org
… algorithms such as multinomial naive bayes logistic regression, K-Nearest neighbour and Support … issue will be solved using automated messages through a chat bot solution … data set was provided, initially un- supervised learning algorithm K-Nearest Neighbor (KNN) clustering …

Enhanced Secure Solution for PoS Architecture
C Samaranayake, RK Achchige… – … on Advancements in …, 2019 – ieeexplore.ieee.org
… This system supported three machine learning algorithms; k- nearest neighbor (k-NN), support vector machine (SVM … enables the option to run basic assessments using a Chatbot interface is … [16] T. Srivastava Analyticsvidhya.com, “Introduction to k-Nearest Neighbors: A powerful …

How artificial intelligence can improve web development and testing
A Stocco – Proceedings of the Conference Companion of the 3rd …, 2019 – dl.acm.org
… hot topic with many practical applications such as self-driving vehicles, voice-assisted control, automated traders, and customer service chatbots … Finally, a k-nearest-neighbors (KNN) algorithm is used to generate a hierarchical GUI structure from which a pro- totype application …

A CONCEPTUAL FRAMEWORK FOR NETWORK TRAFFIC CONTROL AND MONITORING USING ARTIFICIAL NEURAL NETWORKS
UR ALO, SI ELE, HF NWEKE – Journal of Theoretical and Applied …, 2019 – jatit.org
… Typical examples of supervised machine learning approaches recently implemented for network flow include support vector machine, decision tree, Naïve Bayes, k-Nearest Neighbors, artificial neural networks etc. [6]. For instance …

Artificial Intelligence and Machine Learning: Overview and Applications.
R Byrne, D Stracuzzi, W Davis, JP Watson, M Reno… – 2019 – osti.gov
… questioning by the year 2000 June 2014, A chatbot called Eugene Goostman, which simulates a 13-year-old Ukrainian boy, convinced 30% of the judges … 2011 IBM’s Watson beats two legendary humans at Jeopardy 2014 Chatbot Eugene Goostman passes “Turing Test” …

Explaining Content-based Recommendations with Topic Models
GP Polleti, FG Cozman – 2019 8th Brazilian Conference on …, 2019 – ieeexplore.ieee.org
… The recommen- dation system resorts to a k-nearest neighbors model that recommends the k closest … robots to embodied conversational agents 24 6 13 how do you want your chatbot … 1401.1880 [12] M. Volkovs, GW Yu, and T. Poutanen, “Content-based neighbor models for …

Challenging Racist Predictive Policing Algorithms under the Equal Protection Clause
RM O’Donnell – NYUL Rev., 2019 – HeinOnline
… by it- two machine learning candidates are conducive to these goals: K- Nearest Neighbors (KNN) and … 22 KNN algorithms incorporate new variables based on the “nearest neighbor” of the … The algorithm then incorporates the nearest neighbors of the variables into its code and …

A Survey on Predicting Resident Intentions Using Contextual Modalities in Smart Home
RMD Hegde, HH Kenchannavar – International Journal of Advanced …, 2019 – igi-global.com
… RandomForest(99.4%),RidgeLogisticRegression (69.59%),NaiveBase(84.2%),KNearest Neighbours (99.4%),Support … Maurer& Smailagic(nd) eWatch k-NearestNeighbor,DecisionTrees basedC4.5,Bayes … isalsousedtobuildthecustomerchatservicelikechatbotwhichprocesses …

Intelligent software tools for recruiting
SB Kulkarni, X Che – Journal of International …, 2019 – scholarworks.lib.csusb.edu
… Regression Trees (decision trees) (5) Naive Bayes (6) K-Nearest Neighbors (KNN Algorithm) (7 … Some chatbots are equipped with calendars/scheduling software to schedule interviews … Recruiters/talent acquisition professionals usually implement chatbot tools in their employee …

An educational approach to machine learning with mobile applications
K Zhu – 2019 – dspace.mit.edu
… to guide them through developing their own Scratch applications that use machine learning, like image recognition, chatbots, and game playing … is closest to (along with its confidence). Google’s Teachable Machine uses a k-nearest neighbors (KNN) classifier to classify images …

Lifelong Machine Learning Methods And Its Application In Multi-Label Classification
NM Chau – uet.edu.vn
… Applications, for example, intelligent assistants, chatbots, and physical robots that cooperate with humans and systems … kNN k-nearest neighbors NBC Naive Bayes Classifier …

Is there an Optimal Technology to Provide Personal Supportive Feedback in Prevention of Obesity?
S Sandri, H Zheng, F Engel, A Moorhead… – 2019 IEEE …, 2019 – ieeexplore.ieee.org
… Various ML techniques have been applied in this task already, like k-Nearest Neighbors (KNN), Decision Trees, Support Vector Machine (SVM … can I book an appointment this Thursday?” could be a user utterance for a chatbot that books … Intents are what chatbots are made up of …

Artificial Intelligence and Machine Learning: Overview and Applications for Power Systems.
R Byrne, R Byrne, D Stracuzzi, D Stracuzzi, W Davis… – 2019 – osti.gov
… questioning by the year 2000 June 2014, A chatbot called Eugene Goostman, which simulates a 13-year-old Ukrainian boy, convinced 30% of the judges … 2008 2014 First Al Winter Google’s speech Chatbot Eugene Commercial Funding Cuts recognition app Goostman passes …

The application of sentiment analysis and text analytics to customer experience reviews to understand what customers are really saying
C Gallagher, E Furey, K Curran – International Journal of Data …, 2019 – igi-global.com
… predictivecustomeranalyticstodayisbetter thaneverbefore.Datasourcessuchascustomer satisfactionsurveys,socialmediachannels,chatbots, voicecalls … TheK-NearestNeighbour(KNN) techniqueisbasedonthenotionthattheclassificationofan instancewillbeinsomewaylikethose …

Template-based Auto Social Magazine and Video Creation Service
JW Lee, DW Jang, MJ Kim, JS Kim… – Proceedings of the …, 2019 – koreascience.or.kr
… “A new chatbot for customer … of the ACM conference on Human Factors in Computing system, 2017 [2] PB Brandzaeg and A Folstad, “Why people use chatbots” in Proc … [5] V. Hautamaki, I. Karkkainen, P. Franti, “Outlier detection using k-nearest neighbour graph, ” in Proc …

Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging
SJ Al’Aref, K Anchouche, G Singh… – European heart …, 2019 – academic.oup.com
Abstract. Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously.

Automatic Judgement of Neural Network-Generated Image Captions
R Biswas, A Mogadala, M Barz, D Sonntag… – … on Statistical Language …, 2019 – Springer
… The k nearest neighbors are chosen randomly depending upon the amount of oversampling needed … In: CVPR (2015)Google Scholar. 31. Xu, A., Liu, Z., Guo, Y., Sinha, V., Akkiraju, R.: A new chatbot for customer service on social media …

Human Centered Artificial Intelligence: Weaving UX into Algorithmic Decision Making.
R Bond, MD Mulvenna, H Wan, DD Finlay, A Wong… – RoCHI, 2019 – rochi.utcluj.ro
… Techniques such as k-nearest neighbor can also provide rationale since they classify based on similarity to neighbors (prior classified cases) … but speech and chatbot based interfaces have become prevalent due to interaction channels like Facebook messenger and smart …

A Treatise On Conversational AI Agents: Learning From Humans’ Behaviour As A Design Outlook
M Yousef, MA Torad – 2019 International Conference on …, 2019 – ieeexplore.ieee.org
… Recent research in technologies are allowing a chat-bot based smart home system by means of … We have created a simple but beneficial Text-classifier, using k-nearest neighbour algorithm, for … Baby, FA Khan, JN Swathi, “Home automation using IoT and a chatbot using natural …

Admissions test scores and high school grade point average predictive power on students’ grade point average during first year university: A research with …
DH Thu – 2019 – ritsumei.repo.nii.ac.jp
… University utilize artificial intelligence to act as chatbots which help answers students’ … and testing. The decision of k value, or the number of neighbors, can be made after … This research selected K Nearest Neighbor for the method of the neural network …

Devi: Open-source human-robot interface for interactive receptionist systems
R Karunasena, P Sandarenu, M Pinto… – 2019 IEEE 4th …, 2019 – ieeexplore.ieee.org
… The speech recognition, synthesis and natural language processing (NLP) components within the chatbot system assist DEVI to further enhance … ing a deep residual network implementation (Resnet-29) [15], [16] provided by ‘dlib’ [17] and a k-nearest neighbors (KNN) classifier …

Detection and classification of social media-based extremist affiliations using sentiment analysis techniques
S Ahmad, MZ Asghar, FM Alotaibi, I Awan – Human-centric Computing and …, 2019 – Springer
… user’s extremist affiliation by filtering tweets prior to their onward transmission, recommendation or training AI Chatbot from tweets [6] … we experiment with multiple Machine Learning (ML) classifiers such as Random Forest, Support Vector Machine, KN-Neighbors, Naïve Bayes …

Multimodal Analysis and Estimation of Intimate Self-Disclosure
M Soleymani, K Stefanov, SH Kang, J Ondras… – 2019 International …, 2019 – dl.acm.org
… achieved F1-score of 0.67 for recognizing disclosure consid- ering both users and chatbot’s utterances … gesture recognition performed poorly on our data, and we thus opted for a simple and more generalizable machine learning model, the k-nearest neighbors (kNN) classifier …

Bridging the Gap Between Research and Production with CODE
Y Jin, D Wanvarie, PTV Le – … on Knowledge Discovery and Data Mining, 2019 – Springer
… The first one is a K-nearest neighbour approach [16], which finds the users who are most similar to the users who clicked on … For example, the business may require that a chatbot to give a meaningful response 95% of the time while the state-of … Peterson, LE: K-nearest neighbor …

Securing Networks Against Anonymous Invaders
NJ Richardson, LJ Burke – 2019 – apps.dtic.mil
… reflexive behaviors. We will explain our use case involving defensive chatbots, our two … Chapter 4 will detail our experiment implementation and testing procedures using Google’s DialogFlow as our chatbot, a locally hosted website running a Java-based keylogger, and …

R Machine Learning Projects: Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5
SK Chinnamgari – 2019 – books.google.com
… Table of Contents Chapter 2: Predicting Employee Attrition Using Ensemble Models Philosophy behind ensembling 41 42 Getting started Understanding the attrition problem and the dataset 44 44 K-nearest neighbors model for benchmarking the performance Bagging Bagged …

Assessment of deep learning methodology for self-organizing 5g networks
MZ Asghar, M Abbas, K Zeeshan, P Kotilainen… – Applied Sciences, 2019 – mdpi.com
… Traditional machine learning approaches, for example, K Nearest Neighbor, lack the ability to be precisely predictive … Apple has showcased Siri on the market, Google has brought out Google Now, Amazon has Alexa, Facebook has virtual assistants or Chat bot, and Microsoft …

RIPPED: Recursive Intent Propagation using Pretrained Embedding Distances
M Ball – 2019 – cs.brown.edu
… 2. Many domains in which NLU systems are desired contain complex, domain-specific language. For example, consider building a medical chatbot, or designing a virtual legal assistant … 3.2.3 k-Nearest Neighbour The k-nearest neighbours (KNN) classification algorithm is …

The roles bots play in Wikipedia
L Zheng, CM Albano, NM Vora, F Mai… – Proceedings of the ACM …, 2019 – dl.acm.org
… use structural role theory to classify chatbots in Twitch into five roles including … we applied the Binary Relevance kNN (BR) [12], Multi- label k Nearest Neighbours (MLKNN) [57 … this neural network based classifier is generally better than the k-nearest neighbor based classifiers …

A Natural Language Processing Approach for Musical Instruments Recommendation System
A Dahale – 2019 – trap.ncirl.ie
… it with a collaborative-filtering tech- nique: matrix factorization and KNN(k nearest neighbor) … This research involves using chatbot that will recommend items considering user’s sentiment … learners and target learners was calculated to form a proximity-based neighborhood …

A Distributed Multi-Agent System (MAS) Application For continuous and Integrated Big Data Processing
A Shashaj, F Mastrorilli, M Morrelli, G Pansini… – … Conference on Ambient …, 2019 – Springer
… processes of Customer/Citizen Operations (CO), where human operators/users need to interact with virtual ‘bots’ (chatbot, conversational AI … MLlib gives us a library to implement Machine Learning methods (in addition to which there’s a K-nearest Neighbours model implemented …

Advanced Methods of Statistical Machine Learning and Applications
A Fanzott – 2019 – netlibrary.aau.at
… used for categorical variables). For more information on k-nearest neighbours consider … using a 15-nearest neighbours approach and the Bayes classifier. The orange and blue … class. The boundaries in the plots show the nearest neighbour decision rule respectively …

Mental Health Monitoring System using Artificial Intelligence: A Review
V Mody, V Mody – 2019 IEEE 5th International Conference for …, 2019 – ieeexplore.ieee.org
… t differ significantly from other classification methods like Quadratic Bayes Normal, K-Nearest Neighbour and Fisher’s … Chatbots are an efficient way of delivering mental health services via a device … data and inferences from precision therapy as an input to the chatbot along with …

A domain-oriented analysis of the impact of machine learning—the case of retailing
F Weber, R Schütte – Big Data and Cognitive Computing, 2019 – mdpi.com
… Lidl offers a chatbot application called “Margot” applying a recommender system in combination with predictive analytics to recommend wine choices to … At the customer contact and service level, chatbots [29] and voice-supported orders (such as Amazon Echo) [50] are relevant …

Intelligent Systems and Applications: Proceedings of the 2019 Intelligent Systems Conference (IntelliSys)
Y Bi, R Bhatia, S Kapoor – 2019 – books.google.com
… Wu, Huan Li, Hengtian Ding, and Lizhuo Zhang A Hierarchical Missing Value Imputation Method by Correlation-Based K-Nearest Neighbors … User Interface Integration in Controlling IoT Devices Applied to Smart Agriculture: Analysis of a Chatbot System Design …

Towards a Performant Multilingual Model Based on Ensemble Learning to Enhance Sentiment Analysis
O Manad, T Menouer, P Darmon – 2019 IEEE/ACS 16th …, 2019 – ieeexplore.ieee.org
… consists of five of most known super- vised classifiers, Multinomial Naive Bayes (MNB), Logistic Regression (LR), K-Nearest Neighbors (KNN), Support … KNN n neighbors (1, 2 ,3, …, 10) 9 C (10?3, 10?2, 10?1, 1, 10) 10 … Also, to preparing an interactive model for chatbots agents …

Human-Robot Team: Effects of Communication in Analyzing Trust
SD Ciocirlan, R Agrigoroaie… – 2019 28th IEEE …, 2019 – ieeexplore.ieee.org
… The chat-bot used was made using the Dialogflow API4 … Considering [18] the following classifiers were chosen: Random Forest Classifier (RFC), K Nearest Neighbors Classifier (KNNC), Linear Support Vector Classification (LSVC), Decision Tree Classifier (DTC) …

Threat is in the Air: Machine Learning for Wireless Network Applications
L Pajola, L Pasa, M Conti – Proceedings of the ACM Workshop on …, 2019 – dl.acm.org
… in order to de- tect possible attacks over the devices [38]; here we find a k-Nearest Neighbors for the … in the real world where malicious data were used; a famous example is Tay, a Microsoft chat bot lunched on … The aim of the chatbot was to answer to questions made by users …

Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems
A Géron – 2019 – books.google.com
Page 1. 2 TenUspodr n Fa d lo te w Edd 2 f o it r io n Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow Concepts, Tools, and Techniques to Build Intelligent Systems Aurélien Géron Page 2. O’REILLY” Honds …

Artificial intelligence for business
R Akerkar – 2019 – Springer
Page 1. SPRINGER BRIEFS IN BUSINESS 123 Rajendra Akerkar Arti cial Intelligence for Business Page 2. SpringerBriefs in Business Page 3. More information about this series at http://www.springer.com/series/8860 Page 4. Rajendra Akerkar Artificial Intelligence for Business …

Deep learning for anomaly detection: A survey
R Chalapathy, S Chawla – arXiv preprint arXiv:1901.03407, 2019 – arxiv.org
Page 1. DEEP LEARNING FOR ANOMALY DETECTION:ASURVEY APREPRINT Raghavendra Chalapathy University of Sydney, Capital Markets Co-operative Research Centre (CMCRC) rcha9612@uni.sydney.edu.au Sanjay …

Intelligent Conversational Agent Assisted Health Coaching System: The CoachAI Approach
A Fadhil – researchgate.net
… Healthcare chatbots currently are either a mix of both user-only (apps that help a … The initial implementation was based on a K-Nearest Neighbors (KNN) algorithm to create user clusters based … case, the user will get and communicate the activities through the chatbot channel by …

Providing appropriate social support to prevention of depression for highly anxious sufferers
F Hao, G Pang, Y Wu, Z Pi, L Xia… – IEEE Transactions on …, 2019 – ieeexplore.ieee.org
… features. Islam et al. [14] adopted k-nearest neighbor classification technology to monitor the likelihood of a user’s depression from the opinions, photos, and videos shared by users on the Facebook social platform. Yang et al. [15 …

Big Data, Data Mining, Machine Learning Und Predictive Analytics–Ein Konzeptioneller Überblick (Big Data, Data Mining, Machine Learning and Predictive Analytics …
V Brühl – Machine Learning Und Predictive Analytics–Ein …, 2019 – papers.ssrn.com
… werden über Aktoren in physische (Robotik) oder virtuelle Handlungen (z. B. Chatbots) umgesetzt … eingesetzt werden, sind beispielsweise Entscheidungsbaumverfahren, Support Vector Machines (SVM), Diskriminanzanalyse oder „k-nearest neighbors“-Algorithmen (Abbildung …

Natural Language Processing Fundamentals: Build intelligent applications that can interpret the human language to deliver impactful results
S Ghosh, D Gunning – 2019 – books.google.com
… Classifiers….. 89 K-Nearest Neighbors ….. 90 … In those sections, you’ll gain an understanding of how to apply NLP techniques to answer questions, as can be used for chatbots. By the …

Twitter bot detection & categorization-a comparative study of machine learning methods
J Novotny – 2019 – lup.lub.lu.se
… 30 3.7 k-Nearest-Neighbors … Crawlers and scrapers: bots programmed to index and archive web- sites, eg to make the sites accessible via search engines. • Chatbots: programs engaging in interactive dialogue with humans via natural language …

Letting the computers take over: using AI to solve marketing problems
G Overgoor, M Chica, W Rand… – California …, 2019 – journals.sagepub.com
Artificial intelligence (AI) has proven to be useful in many applications from automating cars to providing customer service responses. However, though many firms want to take advantage of AI to im…

Fault Prediction in Android Systems through AI
K Bassuday, M Ahmed – 2019 – gupea.ub.gu.se
… Characteristic AUC Area Under the Curve API Application Programming Interface SCM Source Control Management MLP Multi-Layer Perceptron NN Neural Network RBF Radial Basis Function RF Random Forest DT Decision Tree KNN K-Nearest Neighbour SVM Support …

Deep Exemplar Networks for VQA and VQG
BN Patro, VP Namboodiri – arXiv preprint arXiv:1912.09551, 2019 – arxiv.org
… Generating a natural and engaging question is an interesting and challenging task for a smart robot (like chat-bot) … We used the semantic nearest neighbors in a k-nearest neighbor approach using a KD tree data structure to represent the features …

Machine Learning Architecture to Financial Service Organizations
K Palanivel – 2019 – academia.edu
… NLP powers the voice and text-based interface for virtual assistants and chatbots. NLP is increasingly being used to query data sets as well … The ML can be applied to customer support using chatbots, personalized experience and sentiment analysis …

Understanding the role of artificial intelligence in personalized engagement marketing
V Kumar, B Rajan, R Venkatesan… – California …, 2019 – journals.sagepub.com
This article explores the role of artificial intelligence (AI) in aiding personalized engagement marketing—an approach to create, communicate, and deliver personalized offerings to customers. It pr…

Semantselt kahekordsete küsimuste kindlakstegemine: Quora juhtumi uurimine
NMH Ansari – 2019 – web-proxy.io
… sorting user- generated contents online. It can be helpful to build automatic chatbots that reply to user queries online and thus reduces the human effort by avoiding to cater to each individual’s queries. User can search for their …

Gastroenterology Meets Machine Learning: Status Quo and Quo Vadis
A Adadi, S Adadi, M Berrada – Advances in bioinformatics, 2019 – hindawi.com
… k-Nearest neighbours (KNN) KNN is supervised algorithm that classifies new data by a … being assigned to the class most common amongst its K nearest neighbors measured by a … AI provides other tools including robotic surgical systems, conversational AI (chatbots), and human …

State-of-the-art and adoption of artificial intelligence in retailing
FD Weber, R Schütte – Digital Policy, Regulation and Governance, 2019 – emerald.com
… This is a chatbot called “Margot,” who helps the customer in the choice of … AI-related applications can certainly be observed, for example, chatbots that interact … SMS (2017), “Opinion detection of public sector financial statements using K-nearest neighbors”, Electrical Engineering …

Identifying and Mitigating Bias in Machine Learning Applications
L Bald – 2019 – scholarsbank.uoregon.edu
… ML systems accidentally; within 24 hours of release, a Twitter chat bot using AI technologies … variance. The k-Nearest Neighbor technique works by taking an original data point, using … dataset. These nearest neighbors would then be predicted to be in the same category as …

Personality assessment from social media data: An ensemble model
S Taghikhani – 2019 – search.proquest.com
… They used Nave Bayes, K-nearest Neighbor, and SVM, and reached 0.54 accuracy by combining all the elements and using K-Nearest Neighbor but the highest accuracy concluded … accuracy level by using SVM, K-Nearest Neighbors, and Nave Bayes. Furthermore …

Next-generation wireless networks meet advanced machine learning applications
R Trestian – 2019 – books.google.com
… Component Analysis-Based Outliers Detection Through Neighborhood Voting in … Chapter 13 CHEERBOT: A Step Ahead of Conventional Chatbot … most popular machine learning techniques are: PCA, k-Nearest Neighbour, Support Vector …

Criminal Identification from Video Scene Using Conditional Generative Adversarial Network
MJ Uddin, M Rahman, M Tayaba – 2019 – dspace.daffodilvarsity.edu.bd
… They have created a predictive model to predict crime efficiently through machine learning using KNN(K-nearest neighborhood) & boosted decision tree algorithm. The authors … output data length is different from one another. Question answering systems, chatbots …

Review and performance evaluation of photovoltaic array fault detection and diagnosis techniques
AY Appiah, X Zhang, BBK Ayawli… – International Journal of …, 2019 – hindawi.com
Page 1. Review Article Review and Performance Evaluation of Photovoltaic Array Fault Detection and Diagnosis Techniques Albert Yaw Appiah , 1,2 Xinghua Zhang, 1 Ben Beklisi Kwame Ayawli , 1,3 and Frimpong Kyeremeh 1,2 …

Detecting sentences that may be harmful to children with special needs
M Allouch, A Azaria, R Azoulay – 2019 IEEE 31st International …, 2019 – ieeexplore.ieee.org
… Chkroun and Azaria [5], [6] have developed Safebot, a chatbot system that converses with humans … The methods used in the Voting classifier are: Random forest, Extra trees, K nearest neighbors, SVM, Ridge Classifier, Bayesian inference method, and MLP …

How Technologies Will Change the Way Finance Departments Work: A Target Picture and Guidelines for Digital Finance
MA Eßwein – 2019 – duepublico2.uni-due.de
… 80 4.3. K-nearest neighbors ….. 83 4.4 … IS Information systems IT Information technology KNN k-nearest neighbors (algorithm) KPI Key performance indicator LASSO Least absolute shrinkage and selection operator MAR Missing at random …

MLPXSS: An Integrated XSS-Based Attack Detection Scheme in Web Applications Using Multilayer Perceptron Technique
FMM Mokbal, W Dan, A Imran, L Jiuchuan… – IEEE …, 2019 – ieeexplore.ieee.org
… I. INTRODUCTION Web technology has been increased exponentially in daily volume and interactions involving web-based services, such as self-driving finance in web banking, Chatbots /AI assis- tants and recommendation engines in e-commerce, social networking sites …

METAPHOR-A Multiagent Architecture using IoT and Classification Algorithms for Referral Postoperative Patients
A Lima, T Loureiro, M Fernandez… – 2019 IEEE 31st …, 2019 – ieeexplore.ieee.org
… language processing (NLP), as a chatbot, in order to improve the interaction between mobile agent and the user and increase the knowledge base of the system … Decision Tree 76.8 77.7 77.7 0.72 0.03 K Nearest Neighbors (KNN) 87.5 88 88 0.88 0.16 …

Learning to merge-language and vision: A deep evaluation of the encoder, the role of the two modalities, the role of the training task.
R Shekhar – 2019 – eprints-phd.biblio.unitn.it
… 86 vii Page 14. 5.3 Average nearest neighbour overlap between the encoder mul- timodal representations and the ResNet152 and USE embed … tion’s semantic space using the Representation Similarity Analysis and Nearest Neighbour overlap of the object representation …

LEGAL ISSUES AND COMPUTATIONAL MEASURES AT THE CROSS-SECTION OF AI, LAW AND POLICY
S Rathi – 2019 – web2py.iiit.ac.in
… Interactions: With the growing penetration of chat bots and other interactive … Local models only seek to explain a single decision by the neighborhood around the data point it predicted, and can therefore sometimes disregard large parts of the model in their explanation [15] …

Machine learning methods for adaptive test case generation for Android activities
A Cardone – 2019 – indigo.uic.edu
… 4.4.2 K-Nearest Neighbors … 63 VII COMPOSITION OF THE ACTIVITY CLASSIFICATION DATASET 69 VIII RESULTS USING THE K-NEAREST NEIGHBORS ALGORITHM 75 IX RESULTS USING THE DECISION TREE LEARNING ALGORITHM 80 …

Exploring the value of the Bregman Block Average Co-clustering algorithm for missing value imputation in geo-referenced time series
JM Timmermans – 2019 – dspace.library.uu.nl
… 2.2.2 Neighborhood-based algorithms … both discrete and continuous values. The k-Nearest Neighbour algorithm calculates the distance between each … k-number of nearest neighbours in the distance matrix (Hastie et al., 2009, pp. 463- 474). An advantage of the …

NegBERT: A Transfer Learning Approach for Negation Detection and Scope Resolution
A Khandelwal, S Sawant – arXiv preprint arXiv:1911.04211, 2019 – arxiv.org
… from Sentiment Analysis, where the sentiment of a given sentence is dependent on negation, to query response systems like Chatbots, where negation … They used a k- Nearest Neighbors Classifier with features extracted from the sentence and modified to the task at hand …

Neural Networks with Keras Cookbook: Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots
VK Ayyadevara – 2019 – books.google.com
… Chapter 13: Sequence-to-Sequence Learning Introduction Returning sequences of outputs from a network Building a chatbot Getting ready How to do it… Intent extraction Putting it all together Machine translation Getting ready How to do it …

Query-driven Exploration of Big Graphs
MH Namaki – 2019 – search.proquest.com
… The system thus can provide the second item as an advertisement to the user. Moreover, answering Why-questions in attributed graphs enables chatbots [125] … It has been studied for spatial (range) queries over moving objects [68] and k-nearest neighbors [155] …

Imitation learning from imperfect demonstration
YH Wu, N Charoenphakdee, H Bao… – arXiv preprint arXiv …, 2019 – arxiv.org
… labels. Another related scheme was considered in El-Zahhar and El-Gayar [2010] where they consid- ered soft labels z ? [0,1] as fuzzy inputs and proposed a classification approach based on k-nearest neighbors. This method …

Deep Learning For Dummies
JP Mueller, L Massaron – 2019 – books.google.com
Page 1. Deep Learning by John Paul Mueller and Luca Massaron 0004332690.INDD April 5, 2019 12:10 PM i Trim size: 7.375 in × 9.25 in Page 2. Deep Learning For Dummies® Published by: John Wiley & Sons, Inc., 111 River …

using Python
MPUD Kumar – academia.edu
Page 1. Manaranjan Pradhan U Dinesh Kumar | Manaranjan Pradhan U Dinesh Kumar| Machine Learning using Machine Learning Python using Python Page 2. Machine Learning using Python Page 3. Page 4. Machine Learning using Python Manaranjan Pradhan …

An Educational Programming Environment for Teaching the Principles of Machine Learning using LEGO MINDSTORMS
L Peters – 2019 – researchgate.net
… based on either Python, App Inventor or Scratch. The projects range from games to chatbots to predicting who survived the sinking of the Titanic. Almost all of the … Decision Tree Learning • Support Vector Machine • k-Nearest Neighbours 17 Page 25. 4 Research and Design …

How to overcome modelling and model risk management challenges with artificial intelligence and machine learning
D Mayenberger – Journal of Risk Management in Financial …, 2019 – ingentaconnect.com
… Automated customer servicing: Assign customers to the right service representative by recognising their reason for calling, or chatbots that emulate a … K-nearest neighbour (KNN) is a clustering method that finds groups of similar data points, based on a given distance metric or …

Designing and evaluating recommender systems with the user in the loop
M Jugovac – 2019 – eldorado.tu-dortmund.de
… context, a so-called nearest-neighbor approach [Ama+11] can be used to compare the viewing history of a target user with the viewing histories of other users to find 2.1 Design Philosophies of Recommenders 9 Page 16. a set of users with similar preferences—called neighbors …

Proceedings of the 11th International Workshop” Data analysis methods for software systems”
J Bernatavi?ien? – Vilnius University Proceedings, 2019 – zurnalai.vu.lt
Page 1. 11th International Workshop on DATA ANALYSIS METHODS FOR SOFTWARE SYSTEMS Druskininkai, Lithuania, Hotel “Europa Royale” http://www.mii.lt/DAMSS LITHUANIAN COMPUTER SOCIETY VILNIUS UNIVERSITY …

Predicting User’s Intent from Text using Machine Learning Methods
A Katsalis – 2019 – repository.ihu.edu.gr
… It is a challenge to create a robust model which can deal with problems from other domains. Search engines, spoken language understanding (SLU) systems, chatbots and even robots need models that can predict queries and orders from humans. The understanding …

Artificial Intelligence Basics
T Taulli, M Oni – 2019 – Springer
… in this chapter, we’ll also cover the advanced algo- rithms, such as k-Nearest Neighbor (k-NN … Pitts, on the other hand, grew up in a low-income neighborhood and was even homeless as … type in questions, and ELIZA would provide counsel (this was the first example of a chatbot) …

Reinforcement learning for telescope optimisation
C Blows – 2019 – open.uct.ac.za
… et al. 2014). As an example, we will focus on K-Nearest Neighbours (KNN) … k (Raschka 2015). The k nearest stored data points (data that was used to train the model) is used as a majority classification … like self-driving cars, voice generation, chat-bots and many more. Page 37 …

Practical Machine Learning with Rust: Creating Intelligent Applications in Rust
J Bhattacharjee – 2019 – books.google.com
… 72 2.8.6 Support Vector Machines…..77 2.8.7 KNearest Neighbors…..79 vi Page 7 … 188 5.2 Named Entity Recognition…..201 5.3 Chatbots and Natural Language …

Learn Computer Vision Using OpenCV
S Gollapudi – 2019 – Springer
… Sentiment analysis is usually used to perceive and provide automated help or feedback on how a product such as a book or a movie is doing in the market. • Answering queries or help is used in medicine or retail services, for example in chat bots …

A comparative study of social bot classification techniques
F Örnbratt, J Isaksson, M Willing – 2019 – diva-portal.org
… Many such machine learning algorithms exist; Decision tree, Random forests, Naïve Bayes, K-Nearest Neighbour, Support Vector Machines or k-means … Guilbeault, 2018) have been constructed: ? Web Robots (crawlers) ? Chatbots (natural language based dialog system) …

Challenges in application of machine learning in insurance industry
BR Pavlovi? – Tokovi osiguranja, 2019 – scindeks.ceon.rs
… 3. Allstate22 Osiguravaju?a ku?a „Allstate“ razvila je virtuelnog asistenta, Chat-bot ABIE (skra?eno od engl. Allstate Business Insurance Expert), zasnovanog na metodama mašinskog u?enja, za pomo? svojim agentima u prodaji proizvoda za korporativne klijente …

Group Activity Recognition Using Channel State Information
HA Visserman – 2019 – essay.utwente.nl
… For example, a computer model exists that wrote its own musical [2] and a chatbot has been created that can participate in impro- visational … To achieve this accuracy they made use of the k-nearest neighbors algorithm and a group size of between one and three people [6] …

A deep evolutionary approach to bioinspired classifier optimisation for brain-machine interaction
JJ Bird, DR Faria, LJ Manso, A Ekárt, CD Buckingham – Complexity, 2019 – hindawi.com
… success in classification of epileptic brain activity through generated features as inputs to Naive Bayes, Support Vector Machine, K-Nearest Neighbours, and Linear … affective sentiment based on negative and positive polarities [36] and was used in the application of a chatbot …

Modeling User Behavior on Socio-Technical Systems: Patterns and Anomalies
H Lamba – 2019 – reports-archive.adm.cs.cmu.edu
… 151 9.6.2 Effectiveness on real data . . . . . 152 9.7 Scalability . . . . . 152 9.8 Conclusion . . . . . 153 10 Detecting Chatbots on Livestreaming applications 155 …

Thrilled to Bits: A Review of Emotional Intelligence in AI
T Wiel – 2019 – dspace.library.uu.nl
… voice commands to Siri, receiving a tour from a robotic museum guide or being assisted by online chatbots, people interact … (2017) identified the four most used classifiers in contemporary literature: (1) Quadratic Discriminant Analysis (QDA), (2) k-Nearest Neighbour (KNN), (3 …

Computer Analysis of Images and Patterns: 18th International Conference, CAIP 2019, Salerno, Italy, September 3–5, 2019, Proceedings
M Vento, G Percannella – 2019 – books.google.com
Page 1. Mario Vento Gennaro Percannella (Eds.) Computer Analysis of Images and Patterns 18th International Conference, CAIP 2019 Salerno, Italy, September 3–5, 2019 Proceedings, Part I Page 2. Lecture Notes in Computer …

Dynamic algorithm selection for machine learning on time series
L Dahlberg – 2019 – diva-portal.org
… Amazon, Facebook and Microsoft. Machine learning has applications such as image/voice recognition, personal phone assistances, chatbots, weather forecasts, game AI such as AlphaGo [2] and future prospects such as human-like robots and self-driving cars. Although these …

Cognition and the Structure of Bias
GM Johnson – 2019 – escholarship.org
Page 1. UCLA UCLA Electronic Theses and Dissertations Title Cognition and the Structure of Bias Permalink https://escholarship.org/uc/item/7hf582vz Author Johnson, Gabbrielle Michelle Publication Date 2019 Peer reviewed|Thesis/dissertation eScholarship.org …

Advances on Broad-Band Wireless Computing, Communication and Applications: Proceedings of the 14th International Conference on Broad-Band Wireless …
L Barolli, P Hellinckx, T Enokido – 2019 – books.google.com
Page 1. Lecture Notes in Networks and Systems 97 Leonard Barolli Peter Hellinckx Tomoya Enokido Editors Advances on Broad-Band Wireless Computing, Communication and Applications Proceedings of the 14th International …

Atomistic modelling of precipitation in Ni-base superalloys
E Schmidt – 2019 – repository.cam.ac.uk
… tions for 10 repeated optimization jobs updating model- and hyperparame- ters displaying the 70 best potentials each. Eemb,Al (?) was obtained fitting the entire Al-Ni database. The blue dots in b) indicate nearest neighbor distancesinequilibriumfccAl …

Semantic Feature Extraction Using Multi-Sense Embeddings and Lexical Chains
TL Ruas – 2019 – deepblue.lib.umich.edu
… LC Lexical Chains LR Logistic Regression IDC International Data Corporation IEEE Institute of Electrical and Electronics Engineers K-NN K-Nearest Neighbors LDA Latent Dirichlet Allocation LSID Latter SynsetID ML Machine Learning MWE Multiword Expressions …

Exploring automatic approaches for sentiment lexicon creation for Norwegian
KK Amundsen – 2019 – duo.uio.no
… creation is to identify a set of seed words, which is used to increase the size of the lexicon, by for example extracting their neighbours from a … Another application of sentiment analysis is in the field of chatbots and other systems used for communication (Turney & Littman, 2003) …

Voice analysis and business applications. A state-of-the-art
F FEROLDI – 2019 – politesi.polimi.it
Page 1. POLITECNICO DI MILANO SCHOOL OF INDUSTRIAL AND INFORMATION ENGINEERING MANAGEMENT ENGINEERING MASTER DEGREE VOICE ANALYSIS AND BUSINESS APPLICATIONS A STATE-OF-THE-ART Fabio Feroldi – 876701 Supervisor:? Prof …

Adversarial Anomaly Detection
R Bhargava – 2019 – hammer.figshare.com
… A data point that is in a low density neighborhood is an outlier whereas a data point that lies in … score based on the ratio of the average densities of a data instance’s ? neighbors and … est neighbor based methods is that they are faster because the test instance is classified …

Investigation of attack strategies on geoprivacy with spatial obfuscation
MLJ Mol – 2019 – dspace.library.uu.nl
Page 1. Master thesis Investigation of attack strategies on geoprivacy with spatial obfuscation Maarten Mol 27-02-2019 Page 2. Abstract This research looks into the current state of spatial obfuscation algo- rithms and investigates attack strategies to circumvent them …

Using Machine Learning and Artificial Intelligence in Production Technology
SR Sapkota – 2019 – theseus.fi
… investers have never seen before. Chatbot, tracking goods, analyzing supply chain agent behaviours, tracking the … learning library that contains boosting, decision tree learning, gradient boosting trees, expectation-maximization algorithm, k-nearest neighbour algorithm, naive …

Keras to Kubernetes
D Rao – 2019 – Wiley Online Library
Page 1. Keras to Kubernetes® The Journey of a Machine Learning Model to Production Dattaraj Jagdish Rao Page 2. Keras to Kubernetes®: The Journey of a Machine Learning Model to Production Published by John Wiley & Sons, Inc …

A QA-pair generation system for the incident tickets of a public ICT Shared Service Center
M Lammers – 2019 – essay.utwente.nl
… A chatbot or virtual agent is a system that can answer questions of users and drill … During a conversation with the user, they explore the neighborhood of the sub-graph in order to … SVM and MaxEntropy appeared most useful over Naïve Bayes and K-nearest neighbors’ algorithm …

CERIAS Tech Report 2019-4 Adversarial Anomaly Detectio
R Bhargava – 2019 – cerias.purdue.edu
… A data point that is in a low density neighborhood is an outlier whereas a data point that lies in … score based on the ratio of the average densities of a data instance’s ? neighbors and … est neighbor based methods is that they are faster because the test instance is classified …

Machine-Assisted Learning in Highly-Interdisciplinary Media Fields: A Multimedia Guide on Modern Art
E Chatzara, R Kotsakis, N Tsipas, L Vrysis… – Education …, 2019 – mdpi.com
Art and technology have always been very tightly intertwined, presenting strong influences on each other. On the other hand, technological evolution led to today’s digital media landscape, elaborating mediated communication tools, thus providing new creative means of expression …

Narrative Text Generation via Latent Embedding from Visual Stories
??? – 2019 – s-space.snu.ac.kr
… based on similar approaches (Shaw and Jebara, 2009). Terada and von Luxburg (Terada and Luxburg, 2014) showed that if a k-nearest neighbor graph is given as local ordinal constraints, we can reconstruct the point set. Also, they showed that statistical consistency is valid …

Knowledge Discovery from Big Text Data
E Park – 2019 – unsworks.unsw.edu.au
… Chawla et al. [CBHK02a] proposed a synthetic over-sampling method, namely SMOTE, which generates additional samples based on their nearest neighbors. There are many variants of SMOTE. Borderline-SMOTE generates new samples only among the …

Cognitive Computing Recipes
A Masood, A Hashmi – Springer
Page 1. Cognitive Computing Recipes Artificial Intelligence Solutions Using Microsoft Cognitive Services and TensorFlow — Adnan Masood Adnan Hashmi Foreword by Matt Winkler Page 2. Cognitive Computing Recipes Artificial Intelligence Solutions Using …

Metaphors, Myths and the Stories We Tell: How to Empower a Flourishing AI Enabled Human in the Future of Work by Enabling Whole Brain Thinking
L Shand – 2019 – openresearch.ocadu.ca
… In the greater context, experiments like the Chatbot Tay Tweets demonstrate how algorithms that rely on the current historical vocabulary of human society with its negative undertones … This is also includes how we interact with the digital world with smart speakers and Chatbots …

Unsupervised Learning in Networks, Sequences and Beyond
Y Liu – 2019 – deepblue.lib.umich.edu
… sides. For example, most EM algorithms are generative as they maximize a posterior likelihood while trying to discover the hidden variable; KNN (k-nearest-neighbors) Page 20. 10 is discriminative as it models a conditional probability. Distinction becomes more …

Utility of Artificial Intelligence and Machine Learning in Cybersecurity
FL Loaiza, JD Birdwell, GL Kennedy, D Visser – 2019 – JSTOR
Page 1. INSTITUTE FOR DEFENSE ANALYSES Utility of Artificial Intelligence and Machine Learning in Cybersecurity Francisco L. Loaiza, Project Leader June 2019 Approved for public release; distribution is unlimited. IDA Non-Standard NS D-10694 …

Distributed traffic forecasting using Apache Spark
N Boufidis – 2019 – repository.ihu.edu.gr
… telligence applications like fully or semi-autonomous vehicles, to clever, humanlike chat- bots like Apple’s Siri and Microsoft’s Cortana … Average (ARIMA) or k-Nearest Neighbors model, in the typical and atypical case respec- tively. Sunderrajan et al …

Automatic Detection of Emotions and Distress in Textual Data
E Mohammadi – 2019 – caiac.ca
Page 1. Automatic Detection of Emotions and Distress in Textual Data Elham Mohammadi A Thesis in The Department of Computer Science and Software Engineering Presented in Partial Fulfillment of the Requirements for the Degree of Master of Computer Science at …

BRB based Deep Learning Approach with Application in Sensor Data Streams
S Kabir – 2019 – diva-portal.org
… Evidential Reasoning EU European Union FC Forward Chaining FOPC First Order Predicate Calculus VGG Visual Geometry Group ICT Information and Communication Technology IoT Internet of Things IQA Image Quality Assessment KNN K-Nearest Neighbours LSTM Long …

Surveying the Development of Authorship Identification of Text Messages
A Majma’ah, S Arabia – 2019 – infonomics-society.org
… system performance as a function of text length. They used the k-Nearest Neighbour as classifier; and achieved a 91.5% rate of accuracy in an authorship authentication. However, this shows that the selection of lexical features …

Visual Dialog: Towards Communicative Visual Agents
S Kottur – 2019 – kilthub.cmu.edu
… 8 Page 23. Conversational Modeling and Chatbots. Visual Dialog is the visual analogue of text-based dialog and conversation modeling. While some of the earliest developed chat- bots were rule-based [122], end-to-end learning based approaches are now being actively …

Detecting summary-worthy sentences: the effect of discourse features
M Droog-Hayes, GA Wiggins… – 2019 IEEE 13th …, 2019 – ieeexplore.ieee.org
… 2We also tested ZeroR, Naive Bayes, Sequential Minimal Optimization, K- Nearest Neighbours, the PART rule based algorithm, and the decision tree algorithms REPTree and J48 … 55–60. [21] T. Wolf, “State-of-the-art neural coreference resolution for chatbots,” Jul 2017 …

Reinforcement learning for Dialogue Systems optimization with user adaptation.
N Carrara – 2019 – tel.archives-ouvertes.fr
Page 1. HAL Id: tel-02422691 https://tel.archives-ouvertes.fr/tel-02422691 Submitted on 23 Dec 2019 HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not …

Blockchain: The Untold Story: From birth of Internet to future of Blockchain
S Mahankali – 2019 – books.google.com
… In the process they were the first to solve the double-spending problem for digital currency. Incidentally, Hal Finney is the neighbour of a person by name ‘SATOSHINAKAMOTO’ who did not have any clue about the technology aspects of Bitcoin, when interrogated …

Towards the Learning, Perception, and Effectiveness of Teachable Conversational Agents
N Chhibber – 2019 – uwspace.uwaterloo.ca
Page 1. Towards the Learning, Perception, and Effectiveness of Teachable Conversational Agents by Nalin Chhibber A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Master of Mathematics in Computer Science …

APPLYING NATURAL LANGUAGE PROCESSING IN TEXT BASED SUPPLIER DISCOVERY
J Heikkilä, J Kanniainen – 2019 – trepo.tuni.fi
… Density-Based Spatial Clustering of Applications with Noise KNN K-Nearest Neighbor MCDM Multi … Preference by Similarity to Ideal Solution t-SNE t-Distributional Stochastic Neighbor … to domains like speech recognition, lexical analysis, text summarization, chatbots, text tagging …

Web Engineering: 19th International Conference, ICWE 2019, Daejeon, South Korea, June 11–14, 2019, Proceedings
M Bakaev, F Frasincar, IY Ko – 2019 – books.google.com
… Keywords: Deep learning 4 Technical debt 1 Introduction Deep learning has shown amazing results in many areas including image classification [10], object detection [12], pose estimation, machine translation [4], chatbots [5], sentiment analysis, recommendation [11] and …

Information extraction from short text messages
A Abbas, J Holmberg – LU-CS-EX 2019-18, 2019 – lup.lub.lu.se
… Subsequent versions have added such things as LTE support, group chat functionality, IP voice calls, geolocation push, chatbots, and more … the techniques achieved the following F1 values: 88.78% for decision tree, 87.62% for naive Bayes and 84.24% for k-nearest neighbors …

An Urdu semantic tagger-lexicons, corpora, methods and tools
J Shafi – 2019 – eprints.lancs.ac.uk
… [65], software engineering [227], empirical language analysis [171], requirements engineering [182], historical semantic analysis via HTST 1.1 [166], to train a Chatbot [218], and several others [23, 214]. Moreover, USAS [180] has been ported previously …

Regulating ai and robotics: Ethical and legal challenges
M Ebers – 2019 – papers.ssrn.com
Page 1. 1 Chapter 2 Regulating AI and Robotics: Ethical and Legal Challenges Martin Ebers* in: Martin Ebers/Susana Navas Navarro (eds.), Algorithms and Law, Cambridge, Cambridge University Press, 2019 (forthcoming). Version: 17 April 2019 …

A Partially Automated Process For the Generation of Believable Human Behaviors
B Parsons – 2019 – scholarcommons.sc.edu
… on the observer. What is believable to one human may not be believable to another. Early chatbots, programs that respond to user input with textual conversation … case-based reasoning. These cases are then weighted automatically using a k-nearest neighbor classifier …

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