The question classifier module is a component of a dialog system that is responsible for identifying the type or category of a given question. This module typically receives the user’s input in the form of natural language text, along with any additional context or information that the system has about the user or the current conversation. It then uses natural language processing techniques to analyze the input and determine the type or category of the question.
The question classifier module typically includes a set of rules or algorithms that define how the system should classify different types of questions. For example, the module may use rules to identify common patterns and structures in questions, such as the use of specific words or phrases, or the presence of particular grammatical constructions. It may also use algorithms to identify the underlying intent or purpose of the question, such as whether it is asking for information, seeking confirmation, or requesting an action.
Once the question has been classified, the module generates a set of intermediate representations of the question’s type or category. These representations may take the form of labels or tags, such as “factual” or “opinion,” or more detailed descriptions of the question’s intent or purpose. These representations can then be used by other modules in the system to generate appropriate responses or actions.
Overall, the function of the question classifier module is to help the dialog system identify the type or category of a given question. This can help improve the system’s ability to interpret and respond to a wide range of user input, and make the interaction more natural and effective for the user.
Domain ontology based automatic question answering J Fu, J Xu… – Computer Engineering and Technology, …, 2009 – ieeexplore.ieee.org … classifier, FAQ question matcher, question analyzer, answer extraction based on two strategy, ontology knowledge base, the architecture of system is describe in Fig.1. Users proposed their question in natural language, the question is put to question classifier module in which … Cited by 10 – Related articles – All 3 versions
Using Wikipedia at the TREC QA track [PDF] from uva.nlDD Ahn, V Jijkoun, GA Mishne, KE Muller… – 2005 – dare.uva.nl … the topic. The QUARTZ question classifier module identifies the named entity type that should be returned as an answer to the question; a named entity tagger then identifies potential answers in the encyclopedic entry. The list … Cited by 76 – Related articles – All 14 versions
Bayes risk-based dialogue management for document retrieval system with speech interface [PDF] from aclweb.orgT Misu… – Speech Communication, 2010 – Elsevier … A QA system typically consists of a question classifier module that determines the type of question and an answer extraction module that generates answer candidates from the KB and selects the most appropriate candidates using some scoring function ([Ravichandran and … Cited by 5 – Related articles – All 20 versions
A Vietnamese question answering system [PDF] from vnu.edu.vnDQ Nguyen, SB Pham – Knowledge and Systems …, 2009 – ieeexplore.ieee.org … pattern matcher. The output of this module is the intermediate representation of the input question. a) Question classifier module. Question category is indicative of the answer type. It also guides the answer retrieval module. In … Cited by 1 – Related articles – All 10 versions
[PDF] A Machine Learning Approach for an Indonesian-English Cross Language Question Answering System [PDF] from tut.ac.jpA Purwarianti, M Tsuchiya… – IEICE transactions on …, 2007 – slp.ics.tut.ac.jp … As shown in Fig.1, Indonesian questions are first analyzed by the question an- alyzer into keywords, the main question word, EAT and a phrase-like information. Our question analyzer consists of a question shallow parser and a question classifier module. … Cited by 1 – Related articles – BL Direct – All 11 versions
[PDF] Temporal information needs in ResPubliQA: an attempt to improve accuracy. The UC3M participation at CLEF 2010 [PDF] from clef2010.orgMT Vicente-Díez, JM Schneider… – 2010 – clef2010.org … 100· __ _ _ ___ _ @ Questions of Number Total candidates first nin Answered Correctly n top = (4) • Temporal Question Classification Percentage (TC). This measure estimates the performance of the question classifier module, determining two different values: … Cited by 1 – Related articles – View as HTML – All 4 versions
CINDI: a digital library for academics R Chen, A Perez, K Dutta… – Proceedings of the 2nd Canadian …, 2009 – dl.acm.org … Figure 2. VQAS Architecture ? VQAS takes a natural language question as input (Questions could be posed either in French or English). The Question Classifier module determines the type of question and the type of answer. … Cited by 1 – Related articles
[PDF] A Semantic Question/Answering System using Topic Models [PDF] from berkeley.eduA Celikyilmaz – eecs.berkeley.edu … Before we present our new cluster-based QA model, we briefly explain a typical QA process (pipeline): Initially after a given question is broken down into keywords and semantic groups, eg, subject, object, etc., its answer type is identified via a question classifier module . An … Related articles – View as HTML – All 3 versions
[PDF] Open Domain Factoid Question Answering System [PDF] from aptnk.inA Patanaik – 2009 – aptnk.in … search for the answers. Current QA systems typically include a question classifier module that determines the type of question and the type of answer. After the question is analyzed, the system Page 11. 11 typically uses several … Related articles – View as HTML
[PDF] The DI@ UE’s participation in QA4MRE: from QA to multiple choice challenge [PDF] from clef2011.orgJ Saias… – clef2011.org … The Question Classifier module was thought to determine the type of the question, which is later considered in assessing each response. The Local KB has a starting knowledge base containing common sense facts about places, entities and events. … Related articles – View as HTML
[PDF] The University of Amsterdam at TREC 2004 [PDF] from uva.nlDAVJJ Kamps, G Mishne… – Proceedings of the 13th Text … – staff.science.uva.nl Page 1. The University of Amsterdam at TREC 2004 David Ahn Valentin Jijkoun Jaap Kamps * Gilad Mishne Karin Müller Maarten de Rijke Stefan Schlobach† Informatics Institute, University of Amsterdam Kruislaan 403, 1098 … Cited by 2 – Related articles – View as HTML – All 13 versions
Online Learning of Bayes Risk-Based Optimization of Dialogue Management for Document Retrieval Systems with Speech Interface [PDF] from newbooks-services.deT Misu, K Sugiura, T Kawahara, K Ohtake… – … Technology and Design, 2011 – Springer … A QA system typically consists of a question classifier module that deter- mines the type of question and an answer extraction module that generates answer candidates from the KB and selects the most appropriate candidates us- ing some scoring function (Ravichandran and … Related articles – All 4 versions
Intelligent answering location questions from the web using molecular alignment A Figueroa… – Journal of Intelligent Information Systems, 2010 – Springer … phenomena that can be found in NL documents. Current QA systems typically include a question classifier module that determines the type of question and the type of answer. After the question is analysed, the system typically … Related articles – All 5 versions
Generalized Quantifiers and Natural Language A Badia – Quantifiers in Action, 2009 – Springer … compose an answer. Corresponding to this, most QA systems have an architecture with several discernible components: 1. a question classifier module that determines the type of question and the type of answer. 2. a document …
[PDF] Developing Cross Language Systems for Language Pair with Limited Resource-Indonesian-Japanese CLIR and CLQA [PDF] from tut.ac.jpA Purwarianti – 2007 – slp.ics.tut.ac.jp … The passages with tagged answers in it are also provided. • The system has a question classifier module with machine learning approach for Indonesian language (limited resource language) that achieves good performance. … Related articles – View as HTML
[BOOK] Spoken dialogue systems technology and design W Minker, GG Lee, S Nakamura… – 2010 – books.google.com Page 1. Wolfgang Minker Gary Geunbae Lee Satoshi Nakamura Joseph Mariani Editors Spoken Dialogue Systems Technology and Design Springer Page 2. Spoken Dialogue Systems Technology and Design Page 3. Editors … Cited by 3 – Related articles – Library Search – All 2 versions
[PDF] A syntactic candidate ranking method for answering non-copulative questions [PDF] from concordia.caAK Lamjiri – 2007 – users.encs.concordia.ca Page 1. A SYNTACTIC CANDIDATE RANKING METHOD FOR ANSWERING NON-COPULATIVE QUESTIONS Abolfazl Keighobadi Lamjiri A thesis in The Department of Computer Science and Software Engineering Presented in Partial Fulfillment of the Requirements … Related articles – View as HTML – Library Search – All 4 versions
[PDF] Departamento de Tecnologías y Sistemas de Información UNIVERSIDAD DE CASTILLA LA MANCHA [PDF] from unirioja.esAS Villaverde – dialnet.unirioja.es Page 1. Departamento de Tecnologías y Sistemas de Información UNIVERSIDAD DE CASTILLA LA MANCHA TESIS DOCTORAL Fuzzy Approach to Conceptual Meaning Processing in Natural Language Documents Autor: Andrés … Related articles – View as HTML
[PDF] Semantically enhanced Information Retrieval: an ontology-based approach [PDF] from uam.esMF Sánchez – ir.ii.uam.es Page 1. Escuela Politécnica Superior Departamento de Ingeniería Informática Semantically enhanced Information Retrieval: an ontology-based approach Dissertation written by Miriam Fernández Sánchez Under the supervision of Pablo Castells Azpilicueta … Related articles – View as HTML – All 8 versions