Stemmer & Chatbots


Stemming is a natural language processing technique that involves reducing inflected (or sometimes derived) words to their word stem, base, or root form. This is typically done in order to facilitate the processing and analysis of text data, as it allows words that have the same root or meaning to be treated as the same word, regardless of their inflection or tense.

For example, the word “jumps” could be stemmed to the word “jump,” and the word “jumping” could be stemmed to the same root. This can be useful for tasks such as text classification, information retrieval, and search, as it allows the system to more easily identify and group together related words.

There are several different algorithms and techniques that can be used for stemming, including the Porter stemmer and the Snowball stemmer. These algorithms typically work by identifying and removing common suffixes and inflections from words in order to obtain the base form. It is important to note that stemming can sometimes produce words that are not actual English words, and it may not always produce the most accurate base form of a word. As a result, stemming is often used in conjunction with other techniques, such as lemmatization, in order to achieve more accurate results.

Snowball is a small string processing programming language that was designed specifically for creating stemming algorithms for use in information retrieval. It was developed by Martin Porter and is based on his Porter stemmer algorithm, which is a widely used stemming algorithm for the English language.

Snowball is designed to be easy to use and is intended to be used as a tool for creating custom stemming algorithms for a wide range of languages. It provides a set of simple, flexible, and extensible rules for stemming that can be customized to suit the specific needs of a particular language or application.

In addition to the English language, Snowball has been used to create stemming algorithms for a number of other languages, including Spanish, French, Italian, Dutch, and many others. It is an open-source software package and is freely available for use under a permissive license.

Knowledge harvesting is the process of extracting knowledge and information from various sources, such as text documents, databases, and websites. It is typically used to build and maintain knowledge bases or to support decision-making processes.

Stemming is a natural language processing technique that involves reducing inflected (or sometimes derived) words to their word stem, base, or root form. It is often used in conjunction with knowledge harvesting in order to facilitate the processing and analysis of text data. By reducing words to their base form, stemming can help to group together words that have the same root or meaning, which can make it easier to identify and extract relevant information from text data.

For example, if a knowledge harvesting system is trying to extract information about a particular topic from a large corpus of text data, it may use stemming to identify and group together all of the different forms of a particular word (such as “run,” “runs,” “running,” etc.). This can help the system to more accurately identify and extract relevant information about the topic, as it can treat all of these different forms of the word as the same concept.

Semantic annotation is the process of annotating resources (such as text documents, images, audio files, or video files) with semantic metadata. Semantic metadata is information about the meaning and context of a resource, and it can include information such as the concepts, entities, and relationships that are present in the resource.

Semantic annotation is typically used to facilitate the processing and analysis of resources by machines. For example, a text document that has been annotated with semantic metadata might include information about the entities and concepts mentioned in the document, as well as the relationships between them. This can make it easier for a machine learning system to understand and analyze the content of the document, and it can also make it easier for humans to search and retrieve relevant information from the document.

There are several different approaches to semantic annotation, including manual annotation, which involves adding semantic metadata to resources by hand, and automated annotation, which involves using algorithms or software to extract and add semantic metadata to resources. Semantic annotation is a key component of the semantic web, which is an initiative to make the web more machine-readable and to enable more intelligent and interactive applications.

Stemmers are often used in chatbots to facilitate the processing and analysis of natural language input. A chatbot is a computer program that is designed to mimic conversation with human users, either through text-based or voice-based interactions. In order to understand and respond to user input, chatbots typically rely on natural language processing (NLP) techniques to analyze and interpret the meaning of the user’s words and phrases.

One way that stemmers can be used in chatbots is to help the chatbot identify and group together words that have the same root or meaning. For example, if a user inputs the phrase “I’m running late,” the chatbot might use a stemmer to identify and group together the different forms of the word “run” (such as “run,” “runs,” “running,” etc.). This can help the chatbot to more accurately understand the meaning of the user’s input and to respond appropriately.

Stemmers can also be used in chatbots to improve the efficiency of natural language processing by reducing the number of unique words that need to be analyzed. By reducing words to their base form, stemmers can help to reduce the size of the chatbot’s vocabulary, which can make it easier and faster for the chatbot to process and understand user input.




See also:

Stemmer & Dialog Systems

A medical ChatBot
R Dharwadkar, NA Deshpande – International Journal of Computer …, 2018 –
… Keywords- Medical Chatbot Natural Language Processing, Porter Stemmer Algorithm, Word Order Similarity Between … Patients who feel included, who are interacting through chatbots with the healthcare … The old chatbot are client communications systems and their best effort is …

Chat-bot for college management system using ai
K Bala, M Kumar, S Hulawale… – … Research Journal of …, 2017 –
… Porter stemming algorithm (or ‘Porter stemmer’) is a process for removing suffixes from words in English … “Designing a Chat-bot that Simulates a … of Informatics Engineering STMIK AMIKOM Yogyakarta, Yogyakarta, Indonesia, 2166-0670/16 $31.00 © 2016 IEEE “Chatbot Using A …

An e-business chatbot using AIML and LSA
NT Thomas – 2016 International Conference on Advances in …, 2016 –
… As most of the chatbots are using AIML, he applied LSA to large amount of documents … It’s a difficult task for the developer to give all questions user could possibly ask to the chatbot … Next, stemming of words are done using Porter Stemmer algorithm …

Ontbot: Ontology based chatbot
H Al-Zubaide, AA Issa – International Symposium on …, 2011 –
… Traditional chatbots are domain dependent, the botmaster is responsible on statically handwriting thousands … This will empower our chatbot with all the facilities and advantages of … and widely used stemming algorithms known as Porter stemming algorithm (or ‘Porter stemmer’) …

Enhancing Community Interactions with Data-Driven Chatbots–The DBpedia Chatbot
RG Athreya, AC Ngonga Ngomo… – Companion Proceedings of …, 2018 –
… messages were vectorized for use in the latter clustering step.8 Then the subject of each mes- sage was tokenized and stemmed using the Porter Stemmer within the … OntBot: Ontology based chatbot … A Semantic Layer on Semi- Structured Data Sources for Intuitive Chatbots …

A survey of various chatbot implementation techniques
A Deshpande, A Shahane, D Gadre… – International …, 2017 –
… Then stop word removal is performed by using Porter stemmer algorithm … This approach details the implementation of such an inquisitive chatbot which recognizes missing data from a query … In the existing chatbots, the chat engine uses pattern-matching algorithms to search the …

Using chatbots to assist communication in collaborative networks
C Frommert, A Häfner, J Friedrich, C Zinke – Working Conference on …, 2018 – Springer
… 1 illustrates the benefits of chatbots for organizational processes as it combines data from … This is possible as the chatbot was implemented using a JSON description and can be … input and JSON model, are stemmed using Python NLTK package and porter stemmer [24] before …

An Intelligent Behaviour Shown by Chatbot System for Banking in Vernacular Languages
M Rajbabu, P Prabhuraj, S Jeyabalan – 2019 –
… This proposed chatbot implemented a algorithm called Porter stemmer Algorithm which is used to … [3] Bhavika R. Ranoliya, Nidhi Raghuwanshi, Sanjay Singh, “Chatbot for university … Atiyah, Shaidah Jusoh, Sufyan Almajali, “An Efficient Search for Context-Based Chatbots” 2018.

Automating Student Management System Using ChatBot and RPA Technology
V Gajra, K Lakdawala, R Bhanushali… – Available at SSRN …, 2020 –
… Porter Stemmer Algorithm and Word Order Similarity between Sentences is used for removing the suffixes … integration of unstructured data and providing necessary research ideas in designing the Chatbots … REFERENCES [1] …

Global Journal Of Engineering Science And Researches
K Sreeja, V Sirisha, N Navya, MR Sastry, BVR Murthy… –
… Keywords: Medical Chatbot Natural Language Processing, Porter Stemmer Algorithm, Word Order Similarity Between Sentences … Chatbots have the potential to revolutionize healthcare. An intelligent chatbot can reduce the process and improve the accuracy of symptoms …

Designing Service-Oriented Chatbot Systems Using a Construction Grammar-Driven Natural Language Generation System
MC Jenkins – 2011 –
… There were strong objections to this test, which become known as ”The Turing test”, as well as a relatively large number of people building increasingly more sophisticated chatbots in order to try and pass it. To date, no chatbot has been able to pass the Turing test …

LSTM Based Self-Defending AI Chatbot Providing Anti-Phishing
SS Kovalluri, A Ashok, H Singanamala – Proceedings of the First …, 2018 –
… After detecting the category, each categorized email is transferred to dedicated chatbot rooms. Each category has specially trained chatbots, and they will reply back to the spammers through the mail servers … Also it will perform Stemming by Porter Stemmer [15] algorithm …

Improving response capability of chatbot using twitter
SS Jeong, YS Seo – Journal of Ambient Intelligence and Humanized …, 2019 – Springer
… research stages with respect to the collection feasibility of knowledge data that can be used in chatbots … The affixes (eg, -ed, -ing, and –ion) are removed by using Porter Stemmer (Hardeniya 2015 … in the knowl- edge database, when a user inputs a query in the chatbot, the input …

Building an Enterprise Chatbot
A Singh, K Ramasubramanian, S Shivam – Springer
… Natural language understanding, processing, and generation Page 19. xxii • Learn how to deploy a complete in-house-built chatbot using an open source technology stack like RASA and Botpress (such chatbots avoid sharing any PIIs with any third-party tools) …

State-of-the-Art Approaches for German Language Chat-Bot Development
N Boisgard – 2018 –
… Figure 1.2: The number of publications containing the terms “chatbot”, “chatterbot”, “chat-bot” or “chat bot … to create, host and integrate chat-bot applications, eg using Microsoft’s Bot Framework8 or IBM’s … to get an overview over the current state-of-the-art in the field of chat-bots …

A Novel Approach for Smart Shopping Using Clustering-Based Collaborative Filtering
SM Pande, A Gaikwad – 2018 –
… One of the most widely used stemming algorithms among them is Porter Stemmer … Today Chatbots are accessed by many websites, applications and different platforms … Any client application having a conversation with user input like Chatbot or any other dialog system can pass …

Natural Language Processing (NLP)
T Taulli – Artificial Intelligence Basics, 2019 – Springer
… For reasons such as these, Watson Explorer Engine does not use the Porter stemmer as its English stemmer. 5 … 28. So before deploying a chatbot, there are some factors to consider: Set Expectations: Do not overpromise with the capabilities with chatbots …

Research of text pre-processing methods for preparing data in Russian for machine learning
VA Kozhevnikov, ES Pankratova – ISJ Theoretical & Applied …, 2020 –
… In our work of development chat bot for organizing employee support, we are more interested in the classification of the input message — the definition … The Lancaster algorithm is newer and was published in 1990 and may be slightly more aggressive than the Porter Stemmer …

Automatic online fake news detection combining content and social signals
ML Della Vedova, E Tacchini, S Moret… – … 22nd Conference of …, 2018 –
… Second, we implement our method within a Facebook Mes- senger chatbot and validate it with an external and independent set of fake … Note that we used Python snowball- stemmer (, set- ting the language to Italian since all the text …

Universal Semantic Web Assistant based on Sequence to Sequence Model and Natural Language Understanding
SV Prajwal, G Mamatha, P Ravi… – 2019 9th International …, 2019 –
… Main principle used is Pattern matching to retrieve the response from chatbot. There … Brain file is used for training the chatbots. Cherry … data. The splicing of words is obtained by Porter Stemmer algorithm and matrix is formed …

Processing Open Text Input in a Scripted Communication Scenario
FPM Heemskerk – 2019 –
… 75 Snowball stemmer … Chatbots converse unconfined, a chatbot conversation can go on until a user determines the conversation is over, whereas a scenario has a beginning and an end. 7 Page 12. Machine learning is often used to support chatbots …

Personalized news conversations with the Softbank Pepper
J Gerbscheid, T Groot, J Wessels, R Wever… –
… The end product is a chatbot implemented on a Softbank Nao, specialized to fetch- and … prerequisite for all of these applications that is still underdeveloped in chatbots is personalization … in every keyword is reduced to its stemmed form using the Snowball stemmer [9]. According …

Does similarity matter? The case of answer extraction from technical discussion forums
RC Kanjirathinkal, A Singh, R Gangadharaiah… – … of COLING 2012 …, 2012 –
… Such mined data can be used to provide enhanced access to the forum content, augment chatbot knowledge (Huang et al., 2007 … on the tf-idf representation of the posts, after removing common English stop- words and stemming the words using a Porter Stemmer (Porter, 1980) …

Natural Language Processing, Understanding, and Generation
A Singh, K Ramasubramanian, S Shivam – Building an Enterprise Chatbot, 2019 – Springer
… Some chatbots are heavy on generative responses, and others are built for retrieving information and … Since this book is about building an enterprise chatbot, we will focus more on … For example, in the following example, the Porter stemmer converts the word “sustenance” into …

CLASSY: A Conversational Aware Suggestion System
D Ferreira, M Antunes, D Gomes, RL Aguiar – … Digital Publishing Institute …, 2019 –
… transforms any uppercase letters tokens to the equivalent lowercase one; 4. Stop word filter, that discards or stops the analysis of tokens that are on a given provided stop words list; 5. Snowball Porter Stemmer, which is … 9. Chaves, AP; Gerosa, MA How should my chatbot interact …

Classifying Urgency: A Study in Machine Learning for Classifying the Level of Medical Emergency of an Animal’s Situation
D Strallhofer, J Ahlqvist – 2018 –
… In this project the SnowBall stemmer [18] was used due to it being one of the few stemmers available that relatively accurately stems Swedish words. The snowball stemmer is not a perfect stemmer as it does not find the original …

Tool to Extract and Summarize Methodologies of Research Articles for Visually Impaired Researchers
K Amarawansha, D Dasanayaka… – … on Advancements in …, 2019 –
… The remaining words after removing the stop words are stemmed using the well-known and widely used Porter Stemmer [16] … [14] Bhagwat and Vyas Ajay, “Deep Learning for Chatbots”, 2018 … [15] Ravi, R,” Intelligent Chatbot for Easy Web-Analytics Insights”, In proc …

DeepSumm: a deep learning approach to text summarization
R CAMPO – 2018 –
… From everyday use applications like Google Translate and chatbots like Siri, Cortana and Alexa, to more challenging tasks like YouTube automatic … more and more attention from non-IT industry too, as, for example, many company websites now feature a chatbot for customer …

Industrial Project Report
A Sood, SP Ghrera – 2018 –
… centraliideas while ignoringiirrelevant information. • Createia chat bot using Pasey McParseface, a language parsing deep learning model … negative to neutralito very positive. • Reduce wordsito theiriroot, or stem,iusing Porter Stemmer, or breakiup textiinto …

Efficient answer-annotation for frequent questions
M Zlabinger, N Rekabsaz, S Zlabinger… – … Conference of the Cross …, 2019 – Springer
… The questions originate from a chat-bot system that maps questions to an answer set, namely a static set of Frequently … As preprocessing, for both datasets, we applied stemming via porter stemmer, removed non-alphanumeric characters, and removed stop words (based on a …

Real-time topic and sentiment analysis in human-robot conversation
E Russell – 2015 –
… of the robot’s expressions. Due to these restrictions, rule-based reply methods such as those used in chatbots are avoided, as are domain-specific sentiment analysis classifiers and any … NLTK’s Snowball Stemmer is used on lists of words to remove stopwords …

Efficient Answer-Annotation for Frequent Questions
A Hanbury – … , and Interaction: 10th International Conference of …, 2015 –
… The questions originate from a chat-bot system that maps questions to an answer set, namely a static set of Frequently … As preprocessing, for both datasets, we applied stemming via porter stemmer, removed non-alphanumeric characters, and removed stop words (based on a …

shorttext Documentation
KY Ho – 2020 –
… PuLP (Optimization with PuLP) • PyStemmer (Snowball Stemmer, the package stemming is no longer used) • TensorFlow (TensorFlow, >= 2.0.0) … removing stop words, and • stemming the words (using Porter stemmer). To do this, load the preprocesser generator …

Semi-supervised answer extraction from discussion forums
RC Kanjirathinkal, R Gangadharaiah… – Proceedings of the …, 2013 –
… To minimize this problem, we used Part- Of-Speech (POS) tags of the words to: • Replace all nouns with their POS tags. • Replace all verbs with its root/stemmed (us- ing Porter stemmer (Porter, 1980)) form and its POS tag. For example, restarting be- comes restart VBG …

Automatic IQ Estimation Using Stylometric Methods
PS Abramov, RV Yampolskiy – … of Research on Learning in the Age …, 2019 –
… The calculation of this feature requires a predefined list of words that are considered proficient. We used a SAT preparation list of 5000 words, which was stemmed using NLTK Porter Stemmer (NLTK, 2018) … Text stylometry for chat bot identification and intelligence estimation …

Natural Language Processing with Java: Techniques for building machine learning and neural network models for NLP
RM Reese, AS Bhatia – 2018 –
… 61 Creating a StopWords class 61 Using LingPipe to remove stopwords 64 Using stemming 65 Using the Porter Stemmer 66 Stemming … cores with the Stanford pipeline Creating a pipeline to search text Summary Chapter 12: Creating a Chatbot Chatbot architecture Artificial …

Incremental Improvement of a Question Answering System by Re-ranking Answer Candidates using Machine Learning
M Barz, D Sonntag – arXiv preprint arXiv:1908.10149, 2019 –
… EVORUS learns to select answers from multiple chatbots via crowdsourcing [11]. The result is a chatbot ensemble excels the performance of each individual chatbot … 6 We use default word tokenizer, Snowball stemmer and n-gram extraction of the nltk toolkit [3] 7 We use the …

A new perspective of negotiation-based dialog to enhance metacognitive skills in the context of open learner models
RM Suleman, R Mizoguchi, M Ikeda – International Journal of Artificial …, 2016 – Springer
… Dimitrova 2003). Conversational agents or chatbots were introduced to allow for more flexible and naturalistic negotiations (Kerly and Bull 2006). The natural language interface provided by a chatbot (Kerly et al. 2008b) improves …

The Art of Natural Language Processing: Classical, Modern and Contemporary Approaches to Text Document Classification
A Ferrario, M Naegelin – … to Text Document Classification (March 1 …, 2020 –
… or claims notifications, as well as the possibility of recording customers’ interactions with corporate con- versational assistants (‘chatbots’), provide data … The Porter stemmer21 [45] is a simple and efficient stemming algorithm, which is commonly used in information retrieval …

Intelligent Customer Pathway
S Affolter – 2018 –
… methods. Recent research for customer service is mainly focusing on fully automated service chat bots [23] … problem. With the popularity of deep learning approaches and social media, chatbots for customer service were introduced. Xu et al …

Using supervised machine learning and sentiment analysis techniques to predict homophobia in portuguese tweets
VG Pereira – 2018 –
… algorithms that organize and categorize information), question answering (every day more popular with Siri systems, Ok Google, chat bots and virtual … Stripping off such word endings is called stemming in IR [8]. The most famous stemming algorithm is called Porter stemmer …

Annif: DIY automated subject indexing using multiple algorithms
O Suominen – 2019 –
… NLTK library , which provides a Snowball stemmer that supports 15 different languages … A similar chatbot could also use a custom vocabulary and model which identifies … The API service also enables novel applications, including mobile apps, browser extensions and chatbots …

Improving Automatic Summarization for Low-and Moderate-resource, Morphologically Complex Languages
… considered essential to many businesses—such as machine translation, speech recognition, chat bots, and sentiment analysis—often perform poorly in these languages. Therefore … international communication, question answering for customer service chat bots, filtering …

Hands-On Natural Language Processing with Python: A practical guide to applying deep learning architectures to your NLP applications
R Arumugam, R Shanmugamani – 2018 –
… State-of-the-art abstractive text summarization Summary Chapter The Question-Answering 9: Question-Answering task and Chatbots Using Memory … memory networks for dialog modeling Dialog datasets The bAbI dialog dataset Raw data format Writing a chatbot in TensorFlow …

Natural Language Processing and Machine Learning for Law and Policy Texts
J Nay – Available at SSRN 3438276, 2019 –
… Electronic copy available at: Page 13. 13 words with the Porter stemmer (Porter 1980). A stemmer removes the endings of many words, eg consolidate, consolidated, and consolidating would all be converted to “consolid.” These are …

A system for collection and analysis of opinions in microblog data: a text mining approach
RM Vaidyanathakumar – Towson University Institutional Repository, 2013 –
… Evaluation Metrics: Precision, coverage ? Statistics: Frequencies distribution, estimators ? Applications: WordNet browser, chatbots Language identification is a key task in the text mining process. Successful analysis of extracted …

Design and Implementation of a Web-Based Software for the OPC Unified Architecture Integrated into a Semantic Ques-tion Answering in the Domain of Smart …
O Oruc –
Page 1. Department of Computer Science Data Management System Group Master Thesis Design and Implementation of a Web-Based Software for the OPC Unified Architecture Integrated into a Semantic Ques- tion Answering in the Domain of Smart Factory Orcun Oruc …

Data-Driven Requirements Engineering
KJ Slegten – 2018 –
Page 1. Data-Driven Requirements Engineering Using Natural Language Processing to Automatically organize a large collection of User Feedback Thesis for the master program Business Informatics 2017-2018 Student: Kariem Slegten Studentnumber: 5767202 …

I Say, You Say, We Say: Using Spoken Language to Model Socio-Cognitive Processes during Computer-Supported Collaborative Problem Solving
AEB Stewart, H Vrzakova, C Sun, J Yonehiro… – Proceedings of the …, 2019 –
… First, utterances were tokenized into individual words using the nltk [4] tokenizer. We experimented with whether to perform word stemming, where word variants are reduced to common roots, using the nltk implementation of the Snowball Stemmer [42] …

Computational Analysis of Humour
V Ahuja – 2019 –
… the past 4-5 years, chat-bots and artificial and virtual assistants have grown larger and their capabilities have been improved and grown complex. One of the most ambitious and useful appli- cation of computer humour is to include comical elements in chatbots, virtual assistants …

Two demonstrators are better than one-a social robot that learns to imitate people with different interaction styles
P Liu, DF Glas, T Kanda… – IEEE Transactions on …, 2017 –
… Simultaneously, word-graphs were constructed by using tweets collected from two different domains (ie politics and entertainment) to transform regular chatbot responses to the responses which mimic the speaking styles of those specific domains [28] …

Human-machine collaboration in online customer service–a long-term feedback-based approach
R Graef, M Klier, K Kluge, JF Zolitschka – Electronic Markets, 2020 – Springer
… was fastest (Gladly 2018). In 2018, half of the customers were disappointed with machine-based cus- tomer service such as chatbots, based primarily on the need for fast and yet personal service. As a consequence, companies …

A survey of state-of-the-art approaches for emotion recognition in text
N Alswaidan, MEB Menai – Knowledge and Information Systems, 2020 – Springer
Page 1. Knowledge and Information Systems 0 REGULAR PAPER A survey of state-of-the-art approaches for emotion recognition in text Nourah Alswaidan1 · Mohamed El Bachir Menai1 …

Understanding Topics and Sentiment from Social Media
S Guha – 2016 –
… come up with appropriate chat responses. Rodrigo et al. [60] built a chatbot on Twitter using only message- response pairs of a single user and followed a keyword based approach. Our motivation and approach are quite different …

Modeling Human Group Behavior in Virtual Worlds
F Shah – 2011 –
Page 1. University of Central Florida Electronic Theses and Dissertations Doctoral Dissertation (Open Access) Modeling Human Group Behavior In Virtual Worlds 2011 Fahad Shah University of Central Florida Find similar works at: …