Text Graphs & Natural Language 2015


Notes:

A text graph is a graph representation of a text item, such as document, passage or sentence.

  • NLG Pipeline Architecture

Wikipedia:

See also:

Text Graphs & Natural Language 2014


Semantic similarity from natural language and ontology analysis S Harispe, S Ranwez, S Janaqi… – Synthesis Lectures on …, 2015 – morganclaypool.com Page 1. Semantic Similarity from Natural Language and Ontology Analysis Sébastien Harispe Sylvie Ranwez Stefan Janaqi Jacky Montmain HAR … h Page 2. Page 3. Semantic Similarity from Natural Language and Ontology Analysis Page 4. Page 5. Synthesis Lectures on Human … Cited by 24 Related articles All 6 versions

Representing text for joint embedding of text and knowledge bases K Toutanova, D Chen, P Pantel, P Choudhury… – ACL Association for …, 2015 – Citeseer Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pages 1499–1509, Lisbon, Portugal, 17-21 September 2015. … either source alone in the framework of path-ranking al- gorithms in a combined knowledge base and text graph (Lao et al … Cited by 27 Related articles All 15 versions

Graph-based statistical language model for code AT Nguyen, TN Nguyen – … of the 37th International Conference on …, 2015 – dl.acm.org … window of previously n generated words. N-gram is popularly used for text analysis in natural language processing (NLP). However, source code in a program has well-defined syntax and semantics according to the programming languages. … Cited by 24 Related articles All 6 versions

Discovering relations by entity search in lightweight semantic text graphs M Laclavik, Š Dlugolinský, M Ciglan – Computing and Informatics, 2015 – cai.sk … The idea of building or extracting graphs from text is not new and it is used to accomplish many tasks in Natural Language Processing (NLP) [30] related to tasks in syntax like Part of Speech (POS … In [15], text graphs are used to create signed social network from text discussions. … Cited by 6 Related articles All 5 versions

Reading mathematics representations: An eye-tracking study C Andrá, P Lindström, F Arzarello, K Holmqvist… – International Journal of …, 2015 – Springer … Kintsch’s (1998) distinction between decoding and comprehending a text/graph supports our claim that a graph in mathematics should be … problem addresses the issue of giving sense to representations of mathematical objects in the registers of natural language, symbols, and … Cited by 18 Related articles All 9 versions

Main core retention on graph-of-words for single-document keyword extraction F Rousseau, M Vazirgiannis – European Conference on Information …, 2015 – Springer … To the best of our knowl- edge, this is the first application of graph degeneracy to natural language processing and information retrieval. … 2.2 Graph Representation of Text Graph representations of textual documents have been around for a decade or so and we refer to the work … Cited by 9 Related articles All 2 versions

Protein–protein interaction predictions using text mining methods N Papanikolaou, GA Pavlopoulos, T Theodosiou… – Methods, 2015 – Elsevier … More complex Text Mining (TM) methodologies use advanced dictionaries and generate networks by Natural Language Processing (NLP) of text, considering gene names as nodes and verbs as edges giving a semantic notion on the graphs. … Cited by 19 Related articles All 7 versions

An introduction to social semantic web mining & big data analytics for political attitudes and mentalities research M Schatten, J Ševa, BO ?uri? – European Quarterly of Political Attitudes …, 2015 – bib.irb.hr … According to Ting, “web content mining analyzes content on the web, such as text, graphs, graphics, etc“ (Ting, 2008) wherefore the main technology used in this type of web mining is natural language processing, described in further detail below. … Cited by 8 Related articles All 7 versions

SKILL: A System for Skill Identification and Normalization. M Zhao, F Javed, F Jacob, M McNair – AAAI, 2015 – pdfs.semanticscholar.org … A graph-based ap- proach to skill extraction from text. In Proceedings of Text- Graphs-8 Workshop. In Empirical Methods for Natural Language Processing (EMNLP 2013). Seattle, USA. Magdy, W., Darwish, K., Emam, O., and Hassan, H. 2007. … Cited by 4 Related articles All 3 versions

Exploring actor–object relationships for query-focused multi-document summarization M Valizadeh, P Brazdil – Soft Computing, 2015 – Springer … text{ nonzero }(\mathrm{S})&= \left| {\text{ Link }({S,S_{j} })>=0.0\text{5 }} \right| \, S_{j} \text{ is } \text{ member } \text{ of } \text{ the } \nonumber \\&\quad \text{ graph } \text{ nodes … The parser was produced by the Stanford Natural Language Processing Group (De Marneffe et al. … Cited by 3 Related articles All 3 versions

Short text keyphrase extraction with hypergraphs A Bellaachia, M Al-Dhelaan – Progress in Artificial Intelligence, 2015 – Springer Page 1. Prog Artif Intell (2015) 3:73–87 DOI 10.1007/s13748-014-0058-1 REGULAR PAPER Short text keyphrase extraction with hypergraphs Abdelghani Bellaachia · Mohammed Al-Dhelaan Received: 17 March 2014 / Accepted … Cited by 2 Related articles All 2 versions

Establishing Semantic Similarity of the Cluster Documents and Extracting Key Entities in the Problem of the Semantic Analysis of News Texts AN Soloshenko, YA Orlova, VL Rozaliev… – Modern Applied …, 2015 – ccsenet.org … Keywords: news text, semantic similarity, fuzzy duplicates, shingles, key entities, text graph, semantic analysis, annotation, mind map 1. Introduction … Thus efficient technologies for automated analysis of the information provided in natural language, are of particular interest not … Cited by 2 Related articles All 4 versions

Answering questions based on gradually learned knowledge from the web using lightweight semantics L Loch, P Navrat, A Kovarova – … of the 16th International Conference on …, 2015 – dl.acm.org … Discovering Relations by Entity Search in Lightweight Semantic Text Graphs. In Computing and Informatics, 33(4), 877– 906. [7] Marsland, S. 2011. Machine Learning An Algorithmic Perspective. … Natural language question answering over RDF: a graph data driven approach. … Cited by 1 Related articles

TextRank based search term identification for software change tasks MM Rahman, CK Roy – 2015 IEEE 22nd International …, 2015 – ieeexplore.ieee.org … First, software change requests are generally made by the people outside the development team, and they communicate their requirements through domain level concepts and using natural language texts. A graph-based representation (ie, also called text graph) of the task … Cited by 3 Related articles All 4 versions

Semantic Parsing for Textual Entailment E Lien, M Kouylekov – IWPT 2015, 2015 – aclweb.org … Be- cause inference-based systems are vulnerable to incomplete knowledge in the rule set and errors in the mapping from natural language sentences to … step, the actual alignment is performed with a SPARQL query that tries to match the hy- pothesis graph to the text graph. … Cited by 3 Related articles All 9 versions

TR-LDA: A Cascaded Key-Bigram Extractor for Microblog Summarization Y Wu, H Zhang, B Xu, H Hao… – International Journal of …, 2015 – search.proquest.com … 5, No. 3, June 2015. [8] and TextRank [4], which use PageRank [9] to rank the text graph. … [12] A. Hulth, Improved automatic keyword extraction given more linguistic knowledge, in Proc. the Conference on Empirical Methods in Natural Language Processing, 2003, pp. 216-223. … Cited by 1 Related articles All 3 versions

Learning multi-faceted representations of individuals from heterogeneous evidence using neural networks J Li, A Ritter, D Jurafsky – arXiv preprint arXiv:1510.05198, 2015 – arxiv.org … holds between two uses. In Natural Language Processing, Collobert et al., [11] described a unified paradigm based on word embeddings within which many of NLP inference tasks can be performed. Take Name Entity Recog … Cited by 5 Related articles All 3 versions

Semantic Process Fragments Matching to Assist the Development of Process Variants K Yongsiriwit, M Sellami… – Services Computing (SCC …, 2015 – ieeexplore.ieee.org … to model elements in a natural language making cloud process diverse and heterogeneous. … languages. Moreover, labels of model elements given by process designers in a natural language may imply semantic interoperability. … Cited by 2 Related articles All 4 versions

A Human-annotated Dataset for Evaluating Tweet Ranking Algorithms D Rout, K Bontcheva – Proceedings of the 26th ACM Conference on …, 2015 – dl.acm.org … as a pre-processing stage for TextRank, as the resulting graphs are generally very dense, whereas TextRank performs well on sparser text graphs. … In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 404–411, 2004. … Cited by 1 Related articles

Joint Learning from Video and Caption T Wang, N Shukla, C Xiong – sites.google.com … On the other hand, natural language is full of rich structural information, and is therefore useful for action representation and human-robot dialogue. … Within our spatial knowledge structure, we store spatial key points of each object and link them to the text graph. …

Linking Stanford Typed Dependencies to Support Text Analytics F Zablith, IH Osman – Proceedings of the 24th International Conference …, 2015 – dl.acm.org … Natural language processing (NLP) research has come a long way in performing various sophisticated tasks on text. … Furthermore, the graph nature of RDF representations enables linking auxiliary information (eg polarity) to the specific elements in the text graph. … Related articles All 6 versions

Graph-Based Approach for Cross Domain Text Linking Y Hu, T Nie, D Shen, Y Kou – Asia-Pacific Web Conference, 2015 – Springer … Node weight: text graph is built from natural language text, so we need a tool to evaluate how important a word is to a document in a corpus. Edge weight: the edge weight represents the strength of connection between the vertices corresponding to the edge. … Related articles

Effects of Graph Generation for Unsupervised Non-Contextual Single Document Keyword Extraction N Schluter – atala.org … We have introduced a novel parse text graph for the representation of documents that is shown to perform better in non-contextual … In Proceedings of the 2003 conference on Empirical methods in natural language processing, EMNLP ’03, p. 216–223, Stroudsburg, PA, USA … Related articles

Learning Interface For E-Learning MDA RAHMAN – worldresearchlibrary.org … III. NATURAL LANGUAGE PROCESSING Natural language processing (NLP) is the formulation and investigation of computationally effective mechanisms forcommunication through natural language. … The system outputs text /graphs /video clips on the screen. … Related articles

Sentiment Classification with Graph Sparsity Regularization XY Dai, C Cheng, S Huang, J Chen – International Conference on …, 2015 – Springer … But in vector space model (VSM) or bag-of -features (BOF) model, features are independent of each other when to learn a classifier model. In this paper, we firstly explore the text graph structure which can represent the structural features in natural language text. … Cited by 1 Related articles

Semantic Graph Application to Call Center for Entity-Relation Search T Kawamura, A Ohsuga – Advanced Science Letters, 2015 – ingentaconnect.com … Keywords: Linked Data, Semantic Web, Natural Language Processing, Information Extraction. … Another research, SemScape,10 also uses sev- eral rules based on graph and text features, which are manually generated to convert text data to a graph structure called Text Graph. … Related articles

Graph-Of-Words: Mining And Retrieving Text With Networks Of Features F ROUSSEAU – 2015 – frncsrss.github.io … In Proceedings of the 53rd annual meeting of the association for computational linguistics and the 7th international joint conference on natural language processing. … In Proceedings of the 2015 conference on empirical methods in natural language processing. In EMNLP ’15. … Related articles

Content-based Information Retrieval by Named Entity Recognition and Verb Semantic Role Labelling GS Mahalakshmi – Journal of Universal Computer Science, 2015 – jucs.org … Processing of Tamil medical documents will be a challenging task in the field of Natural Language Processing (NLP). … In the graph based models [Blanco & Lioma, 12], documents are represented as a text graph and the ranking properties of graph theory such as average path … Cited by 1 Related articles All 5 versions

Empirical Evaluation of Alias Extraction Techniques for Web Based Pervious Name Extraction A Suruliandi, P Selvaperumal – ijisis.org … use of extracted previous names of an entity is useful in improving the performance of a number of natural language processing applications like … Bollegala et al, [21] used twenty three features of which eighteen are calculated from anchor text graph and four are calculated using … Related articles All 2 versions

Concept relation extraction using Naïve Bayes classifier for ontology-based question answering systems G Zayaraz – Journal of King Saud University-Computer and …, 2015 – Elsevier … 1. Introduction. Question answering (QA) systems are considered more complex than information retrieval (IR) systems and require extensive natural language processing techniques to provide an accurate answer to the natural language questions. … Cited by 2 Related articles All 3 versions

Ant colony algorithm for Arabic word sense disambiguation through English lexical information A Bakhouche, T Yamina, D Schwab… – … Journal of Metadata …, 2015 – inderscienceonline.com … It is a difficult language that could hinder the development of tools for the application of natural language processing. The Arabic language has many particularities such as short vowels, the absence of capital letters and complex morphology. … Construction of the text graph … Related articles All 2 versions

Summary Sentence Classification Using Stylometry R Shams, RE Mercer – 2015 IEEE 14th International …, 2015 – ieeexplore.ieee.org … Keywords—Summarization, classification, machine learning, data mining, natural language processing, text mining, stylometry. … 14 Stylometry Model 18.0 98.4 30.4 89.4 0.108 0.017 0.983 0.397 15 Text Graph Model 19.0 62.0 30.0 16 Columbia Summarizer 19.0 14.7 16.6 … Related articles

Sentiment prediction based on valence and arousal using concept search engine P Ajitha, G Gunasekaran – … and Control (ISCO), 2015 IEEE 9th …, 2015 – ieeexplore.ieee.org … [3] AB. Goldberg and X. Zhu, “Seeing Stars When There Aren’t Many Stars: Graph-Based Semi-Supervised Learning for Sentiment Categorization, ” Proc. First Workshop Graph Based Methods for Natural Language Processing (Text Graphs ’06), pp. 45-52, 2006. … Related articles

Automated Mind Map Generation from News Texts Based on Link Grammar AN Soloshenko, YA Orlova, VL Rozaliev… – Creativity in Intelligent, …, 2015 – Springer … 1. Building the graph based on the original text in natural language; 2. Approximate calculation of PageRank values to build a graph; 3. Application of obtained vertex weights to retrieve information from the text. … Figure 5 shows an example of such text graph. … Related articles

Automated Processes for Evaluating the Realism of High-Interaction Honeyfiles B Whitham, T Turner, L Brown – ECCWS2015-Proceedings of the …, 2015 – books.google.com … For instance, Stribling, Krohn and Aguayo (2005) developed an automatic computer-science paper generator, called SCIGen. SCIGen constructed entire academic publications, including text, graphs, figures, and citations. … NLTK: The natural language toolkit. … Cited by 2 Related articles

Social Media Visual Analytics for Emergency Management: A Systematic Mapping M Marbouti, TD Hellmann, F Maurer – ase.cpsc.ucalgary.ca … classifies recent visual analytics works into a set of application categories including Space and Time, Multivariate, Text, Graph and Network … Publications in Natural Language Processing (NLP) venues focus on applying NLP techniques to extract events and stories from the text … Related articles

Graph-Based Concept Clustering for Web Search Results S Jinarat, C Haruechaiyasak… – International Journal of …, 2015 – search.proquest.com … In this paper, we proposed the clustering algorithm for short text, Graph-based concept clustering, which consists of 4 primary steps as … in a Maximum Entropy Part-of-Speech Tagger, In The Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and … Related articles All 3 versions

BigDataBench: An Open-source BigDataBench: An Open-source Big Data Benchmark Suite J Zhan – pdfs.semanticscholar.org Page 1. BigDataBench: An Open-source BigDataBench: An Open-source Big Data Benchmark Suite Jianfeng Zhan INS T ITU T http://prof.ict.ac.cn/BigDataBench TE O F CO MPUTIN G Professor, ICT, Chinese Academy of Sciences … All 2 versions

Big data and the regulation of financial markets S O’Halloran, S Maskey, G McAllister… – 2015 IEEE/ACM …, 2015 – ieeexplore.ieee.org … when coding laws. A. Data Representation Using Natural Language Processing We apply ML methods to the financial regulation database to automatically predict a law’s discretion level based on the text. First, however, we … Related articles All 5 versions

Identifying Dwarfs Workloads in Big Data Analytics W Gao, C Luo, J Zhan, H Ye, X He, L Wang… – arXiv preprint arXiv: …, 2015 – arxiv.org … used technologies in these domains (ie, machine learning, data mining, deep learning, computer vision, natural language processing, information … of different types (ie, struc- tured, semi-structured, and unstructured), and different semantics (eg, text, graph, table, multimedia data … Related articles All 4 versions

Semantic association ranking schemes for information retrieval applications using term association graph representation K Veningston, R Shanmugalakshmi, V Nirmala – Sadhana, 2015 – Springer … TextRank (Mihalcea & Tarau 2004) is a graph-based ranking model for natural language text processing. The algorithm takes into account edge weights while computing the score associated with a vertex in the text graph. Random … Cited by 1 Related articles All 3 versions

Framework on Extracting Personal Name Pseudonyms from the Web MMM Iqbal, K Latha – dl.caasr.org … [234] 2.9 Measuring Semantic Similarity Semantic similarity measures play significant roles in information retrieval and Natural Language Processing. … alias using three different approaches: (1) lexical pattern frequency (2) Word Co-occurrences in an anchor text graph, and (3 … Related articles

A graph based representative keywords extraction model from news articles K Kwon, CH Choi, J Lee, J Jeong, WS Cho – Proceedings of the 2015 …, 2015 – dl.acm.org … Text graphs conforms words and its relationships as a vertex and edge, respectively. … TextRank algorithm is a modified algorithm of the PageRank algorithm of Google [11] to apply to natural language process [12]. Let a graph, G=(V, E) be a directed graph. …

Anti-Summaries: Enhancing Graph-Based Techniques for Summary Extraction with Sentiment Polarity F Hamid, P Tarau – International Conference on Intelligent Text Processing …, 2015 – Springer … The lexical definition and semantic interactions of one word to others help defining edges of the text-graph. … Graph based ranking algorithms have recently gained popularity in various natural language processing applications; specially in generating extractive summaries, select … Cited by 1 Related articles All 2 versions

A Web Robot for Extracting Personal Name Aliases M Thangaraj, PG Sivagaminathan – International Journal of Applied …, 2015 – academia.edu … Traditional information extraction normally takes advantage of Natural Language Processing [NLP] techniques such as lexicons and grammars, whereas web information extraction [31 … (1) Lexical pattern frequency (2) Word co-occurrences in an anchor text graph (3) Page … Cited by 2 Related articles

Grand Challenge: Producing Meaningful Texts C Allen, S Kuebler, L Moss – grandchallenges.iu.edu … history. In her history research, she uses natural language processing to explore conflict in medieval European history. … Page 9. mation such as text, graphs, diagrams, and simulations in shaping both problem solving and learning. Simon … All 3 versions

Empirical Evaluation of Web Based Alias Extraction Techniques D Rajkumar – International Journal of Computer and Electrical …, 2015 – search.proquest.com … This method mainly relies on anchor text graph mined from the web. For implementing the above work, instead of anchor text graph, web structure graph was constructed. … Proceedings of Fifth Conference on Applied Natural Language Processing (pp. 202-208). … Related articles All 2 versions

Information Retrieval of a Name by using its Aliases using Pattern Extraction Algorithm AM Jaiswal, AB Raut – Citeseer … the best aliases among the extracted candidates, the authors propose numerous ranking scores based upon three approaches: – lexical pattern frequency – word co-occurrences in an anchor text graph – page counts … Computational Natural Language Learning (CoNLL’03), pp. …

Next Generation Business Intelligence Techniques in the Concept of Web Engineering of Data Mining MV Kamal, P Srikanth, D Vasumathi – pdfs.semanticscholar.org … implementation tools improves software debugging business rules for novel projects and also presents strategies for efficient study text, graph mining. … Text mining is concerned with the task of extracting relevant information from natural language text and to search for interesting …

Abstractive Multi-Document Text Summarization Using Automatic Text Summarizer Algorithm S Sridevi, S Priya – jrret.com … attempts to develop an understanding of the main concepts in a document and then express those concepts in clear natural language. … unit to the given query was calculated by the cosine similarity and characterized by the corresponding text vertex in a three-layer text graph. … Related articles

Towards a web-scale data management ecosystem demonstrated by SAP HANA F Faerber, J Dees, M Weidner… – 2015 IEEE 31st …, 2015 – ieeexplore.ieee.org … The section will highlight some of the non-standard processing engines like text, graph, or capabilities for processing time series data efficiently. … and sentiments from documents with a rule based approach on top of the natural language functionality. … Cited by 1 Related articles All 2 versions

Topic Modeling for Large-Scale Multimedia Analysis and Retrieval. J Hu, Y Fang, N Ling, L Song – 2015 – books.google.com … for basic tasks such as classification, retrieval, and prediction has become ever popular for multimedia sources in the form of text, graph- ics, images … In natural language processing, a topic model refers to a type of statistical model for representing a col- lection of documents by … Related articles

Ranking Model for Domain Specific Search P Jadhav, V Pawar, C Jadhav, N Sharma – pdfs.semanticscholar.org … various ranking scores to measure the association between a name and a candidate alias using three different approaches: lexical pattern frequency, word co-occurrences in an anchor text graph and page … Empirical Methods in Natural Language Processing (EMNLP ’06), pp. …

Effectively classifying short texts by structured sparse representation with dictionary filtering L Gao, S Zhou, J Guan – Information Sciences, 2015 – Elsevier … A major problem with such a method is that link information is not always available. For example, we cannot establish text graphs for the Reuters and 20Newsgroup corpora. So the graph-based method is not applicable for all STC scenarios. 2.4. … Cited by 1 Related articles All 3 versions

Towards Intelligent Text Mining: Under Limited Linguistic Resources N Kumar – 2015 – web2py.iiit.ac.in … At the same time, incorporating syntactic and semantic role information in the building of the text graph lead to superior results over plain TF*IDF induced cosine similarity (Chali and Joty, 2008). … In phrase graph representation, we treat every distinct phrase as node of the graph. … Related articles

DICH: A framework for discovering implicit communities hidden in tweets D Peng, X Lei, T Huang – World Wide Web, 2015 – Springer … 4.1 Feature selection In natural language processing, a word is the smallest meaningful unit that can be used inde- pendently [7]. An English sentence is formed with words separated with a space. Thus, it is easy to get the individual words from the sentence. … Cited by 2 Related articles All 3 versions

Visualization Of Data Flow Graphs For In-Situ Analysis J Edwards – 2015 – it4bi.univ-tours.fr Page 1. VISUALIZATION OF DATA FLOW GRAPHS FOR IN-SITU ANALYSIS MASTER THESIS by Jacob Edwards Submitted to the Faculty IV, Electrical Engineering and Computer Science Database Systems and Information … Related articles

Tell me why: uma arquitetura para fornecer explicações ricas sobre revisões V Woloszyn – 2015 – lume.ufrgs.br … 2. Data Mining. 3. Natural Language Pro- cessing. 4. Natural Language Generation. 5. Big Data. … domain. The output of our architecture consists of personalized statement using Natural Language Gen- eration that explain people’s opinion about a particular item. … Related articles

Approaching the Definite HJ Pirner – The Unknown as an Engine for Science, 2015 – Springer … For that, a semantic Web is in planning which will attempt to analyze meanings using computers. Linking up information from different sources can lead to discoveries. Speech recognition and natural language translation are at the forefront of semantic web applications. … Related articles

Semantic Concept Recognition From Structured And Unstructured Inputs Within Cyber Security Domain ALPG HO-SUCU – 2015 – etd.lib.metu.edu.tr … ARQ A SPARQL Processor for Jena NLP Natural Language Processing OWL … connection with the Semantic Web”. These disciplines are including knowledge representation, logic, philosophy, databases, machine learning, natural language processing, image processing, etc. … Related articles

An innovative drought early warning system for sub-Saharan Africa: Integrating modern and indigenous approaches M Masinde – African Journal of Science, Technology, Innovation …, 2015 – Taylor & Francis Cited by 5 Related articles All 3 versions

Argumentation-Based Computer Supported Collaborative Learning (ABCSCL): A synthesis of 15 years of research A Weinberger, HJA Biemans, M Mulder, M Chizari – mmulder.nl … structure of a well-formed sentence. Toulmin proposed his model as an alternative to the standard interpretation of for- mal logic, with the aim of analyzing real-world argumentation in natural language. Despite the influential role of … Related articles

NSF Sponsored Workshop: Research Issues at the Boundary of AI and Robotics N Amato, S Koenig, D Shell – robotics.cs.tamu.edu Page 1. NSF Sponsored Workshop: Research Issues at the Boundary of AI and Robotics Nancy Amato, amatao@tamu.edu Sven Koenig, skoenig@usc.edu Dylan Shell, dshell@cs.tamu.edu Introduction The National Science … Related articles All 2 versions

A comparative study of decision Tree and Naïve Bayesian Classifiers on Verbal Autopsy Datasets G Ondego – 2015 – erepository.uonbi.ac.ke Page 1. UNIVERSITY OF NAIROBI SCHOOL OF COMPUTING AND INFORMATICS A COMPARATIVE STUDY OF DECISION TREE AND NAÏVE BAYESIAN CLASSIFIERS ON VERBAL AUTOPSY DATASETS BY GORDON OUMA ONDEGO … Related articles

[BOOK] Smart Technologies and the End (s) of Law: Novel Entanglements of Law and Technology M Hildebrandt – 2015 – books.google.com … scanning the automatically composed summary of a report, sent to her office late last night – uploaded into Toma, which has put the doc onscreen on the back of her suitcase (monitors and terminals have been replaced by surfaces capable of displaying text, graphs and images … Cited by 12 Related articles All 3 versions

Personalisation, Trust, Influence, Reliance, Reputation, and Ethics. Google Semantic Search P Ivory – 2015 – content.grin.com Page 1. Pierce Ivory Personalisation,Trust, Influence, Reliance, Reputation, and Ethics. Google Semantic Search An Irish Discussion Master’s Thesis Media Page 2. Page 3. Bibliographic information published by the German National Library: … Related articles

[BOOK] Learning Data Mining with Python R Layton – 2015 – books.google.com … Table of Contents Chapter 5 – Extracting Features with Transformers Adding noise Vowpal Wabbit Chapter 6 – Social Media Insight Using Naive Bayes Spam detection Natural language processing and part-of-speech tagging Chapter 7 – Discovering Accounts to Follow Using … Cited by 2 Related articles All 4 versions

Semiotics of Politics: Dialogicality of Parliamentary Talk J Turunen – 2015 – diva-portal.org Page 1. ACTA UNIVERSITATIS UPSALIENSIS Skrifter utgivna av Statsvetenskapliga föreningen i Uppsala 191 Page 2. Page 3. Jaakko Turunen Semiotics of Politics Dialogicality of Parliamentary Talk Page 4. Dissertation presented … Related articles All 2 versions