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Sreelakshmi V .
2014 International Journal of Research in Engineering and Technology  
A typical QA system uses several language processing techniques. In this paper, an Open Domain Question Answering that answers simple Wh-questions using online search has been proposed.  ...  Search engines only provide the actual facts as a ranked list of documents and links that contain the keywords. However, what a user really wants is often a precise answer to a question.  ...  Semantic Role Labeling RESULT A simple QA system that answers simple factoid questions was implemented in Python. For the purpose of Semantic Role Labelling, SENNA [20] tool was used.  ... 
doi:10.15623/ijret.2014.0327020 fatcat:gh6rmuuz4jbxvmgubmyl6vttga

Knowledge Authoring and Question Answering with KALM [article]

Tiantian Gao
2019 arXiv   pre-print
Although there is a number of systems developed for knowledge extraction and question answering, they mainly fail in that these system don't achieve high enough accuracy whereas KRR is highly sensitive  ...  In this thesis proposal, I will present Knowledge Authoring Logic Machine (KALM), a rule-based system which allows the user to author knowledge and query the KB in text.  ...  Based on the extracted frame instance, the role-filler disambiguation module disambiguates the meaning of each role-filler word for the corresponding frame role a BabelNet Synset ID.  ... 
arXiv:1905.00840v2 fatcat:tvpkedlzozfajneedyjon7nnwi

A Knowledge-Based Sense Disambiguation Method to Semantically Enhanced NL Question for Restricted Domain

Ammar Arbaaeen, Asadullah Shah
2021 Information  
Extracting the lexical semantic of a Natural Language (NL) question presents challenges at syntactic and semantic levels for most QA systems.  ...  Within the space of question answering (QA) systems, the most critical module to improve overall performance is question analysis processing.  ...  The answer processing module is the final phase in the QA system, that uses the output analysis results to extract a precise and concise answer based on the NL question's structured representation and  ... 
doi:10.3390/info12110452 fatcat:ynxlsrfstrh77mod64243nxoge

A Hybrid Question Answering System

Waheeb Ahmed, P. Babu Anto
2019 Current Journal of Applied Science and Technology  
In this study, we propose a hybrid Question Answering (QA) system for Arabic language. The system combines textual and structured knowledge-Base (KB) data for question answering.  ...  Using these modules, we can query two types of information sources: knowledge bases, and web text.  ...  In order to extract triples from unstructured text, we use the semantic role labels of a sentence and the dependency tree.  ... 
doi:10.9734/cjast/2019/v34i330129 fatcat:g3hnnq6syffirezy2frulsph6y

A Survey on Why-Type Question Answering Systems [article]

Manvi Breja, Sanjay Kumar Jain
2019 arXiv   pre-print
Question Answering Systems reduce the time taken to get an answer, to a query asked in natural language by providing the one most relevant answer.  ...  The paper presents a survey on Why-type Question Answering System, details the architecture, the processes involved in the system and suggests further areas of research.  ...  Many researches have proposed a lot of taxonomies based on different factors for factoid type QA while limited work has been done in non-factoid QA.  ... 
arXiv:1911.04879v1 fatcat:wdvngfqkqvgfvmjn67adebwtqi

Question Answering System using Multiple Information Source and Open Type Answer Merge

Seonyeong Park, Soonchoul Kwon, Byungsoo Kim, Sangdo Han, Hyosup Shim, Gary Geunbae Lee
2015 Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations  
We develop open semantic answer type detector for answer merging and improve previous developed single QA modules such as knowledge base based QA, information retrieval based QA.  ...  This paper presents a multi-strategy and multisource question answering (QA) system that can use multiple strategies to both answer natural language (NL) questions and respond to keywords.  ...  Acknowledgments This work was supported by the ICT R&D program of MSIP/IITP [R0101-15-0176, Development of Core Technology for Human-like Selftaught Learning based on a Symbolic Approach].  ... 
doi:10.3115/v1/n15-3023 dblp:conf/naacl/ParkKKHSL15 fatcat:2jqfj44syvd3xev4fae56eep4i

A supervised learning approach to biological question answering

Ryan T.K. Lin, Justin Liang-Te Chiu, Hong-Jie Dai, Richard Tzong-Han Tsai, Min-Yuh Day, Wen-Lian Hsu, S.H. Rubin, S.-C. Chen
2009 Integrated Computer-Aided Engineering  
First, a factoid QA system is developed to employ a named entity recognition module to extract answer candidates and a linear model to rank them.  ...  Question answering (QA) systems can offer more efficient and user-friendly ways of retrieving such information. Two contributions are provided in this paper.  ...  Acknowledgments This research was supported in part by the National Science Council of Taiwan under grant NSC96-2752-E-001-001-PAE and NSC97-2218-E-155-001, as well as the Thematic Program of Academia  ... 
doi:10.3233/ica-2009-0316 fatcat:2vpfd7xymze4dpvt6uuh3slccy

Biomedical question answering: A survey

Sofia J. Athenikos, Hyoil Han
2010 Computer Methods and Programs in Biomedicine  
Objectives: In this survey, we reviewed the current state of the art in biomedical QA (Question Answering), within a broader framework of semantic knowledge-based QA approaches, and projected directions  ...  Based on the framework, we first conducted a survey of open-domain or non-biomedical-domain QA approaches that belong to each of the three subcategories.  ...  The synthesizer (or extractor) module constructs a semantic graph, based on the semantic role labeling and the semantic information on the documents and the question text.  ... 
doi:10.1016/j.cmpb.2009.10.003 pmid:19913938 fatcat:tv4sel4llbcnjppnn7g2tygqze

Improving Question Answering System based on a Hybrid Technique

Ayatallah Gamal Abass, Sameh Abd El-Ghany, Ahmed Abo Elfetoh
2018 Journal of Computer Science  
Question Answering (QA) is a specialized form of information retrieval characterized by information needs that are expressed as natural language statements or questions.  ...  This hybrid rule base takes into account both the exact match of association rules and the hierarchical match of semantic similarity to overcome the mismatch problem between questions and answer words.  ...  Proposed Method This association rule based questions answering model is based on two knowledge sources.  ... 
doi:10.3844/jcssp.2018.1202.1212 fatcat:bhxfsv6fcfemrktbzuyk63vkja

Developing an Intelligent Question Answering System

Waheeb Ahmed, Ajusha Dasan, Babu Anto P
2017 International Journal of Education and Management Engineering  
The source of knowledge of our system is the World Wide Web(WWW). The system can also understand and respond to more sophisticated questions that need a kind of temporal inference.  ...  For developing such kind of system, it should be able to answer, and store these questions along with their answers.  ...  The answer extraction module The main role of this module is to retrieve data from the Web based on the search terms extracted from the question (as a part of the output of the question analysis module  ... 
doi:10.5815/ijeme.2017.06.06 fatcat:5dgensshhvcafmtcd2w36wmfnq

Design of the Effective Question Answering System by Performing Question Analysis using the Classifier

Gayatri Chavan, Sonal Gore
2016 International Journal of Computer Applications  
There are two main steps of implementation of the proposed question answering system.  ...  The system uses named entity normalization, part-of-speech tagging, and a statistical classifier trained on data from the TREC QA task.  ...  The main focus of a proposed QA system in question analysis phase, where information extraction (answer) done from structured database.  ... 
doi:10.5120/ijca2016908801 fatcat:b6j5cdrtyjfwbkpvrcafyxk5hu

SRLGRN: Semantic Role Labeling Graph Reasoning Network [article]

Chen Zheng, Parisa Kordjamshidi
2020 arXiv   pre-print
We propose a graph reasoning network based on the semantic structure of the sentences to learn cross paragraph reasoning paths and find the supporting facts and the answer jointly.  ...  The proposed graph is a heterogeneous document-level graph that contains nodes of type sentence (question, title, and other sentences), and semantic role labeling sub-graphs per sentence that contain arguments  ...  Acknowledgments This project is supported by National Science Foundation (NSF) CAREER award #1845771 and (partially) supported by the Office of Naval Research grant #N00014-19-1-2308.  ... 
arXiv:2010.03604v2 fatcat:z3nw25dmn5aghfdfbluslflbl4

BESearch: A Supervised Learning Approach to Search for Molecular Event Participants

Richard Tzong-Han Tsai, Hong-Jei Dai, Hsi-Chuan Hung, Ryan T.K. Lin, Wen-Chi Chou, Ying-Shan Su, Min-Yuh Day, Wen-Lian Hsu
2007 2007 IEEE International Conference on Information Reuse and Integration  
Two semantic features, named entity types and semantic roles, are incorporated into the model to help match a query with entities in relevant documents.  ...  In this paper, we propose a novel search system with a new search interface and answer ranking scheme.  ...  It employs two extraction technologies: named entity recognition (NER) and semantic role labeling (SRL). NER is used for extracting candidate NEs.  ... 
doi:10.1109/iri.2007.4296655 dblp:conf/iri/TsaiDHLCSDH07 fatcat:biisuc6eenc6nlbgy6nu5tmshu

Biological question answering with syntactic and semantic feature matching and an improved mean reciprocal ranking measurement

Ryan T.K. Lin, Justin Liang-Te Chiu, Hong-Jei Dai, Min-Yuh Day, Richard Tzong-Han Tsai, Wen-Lian Hsu
2008 2008 IEEE International Conference on Information Reuse and Integration  
To resolve this problem" we propose a question answering (QA) system that offers more efficient and user-friendly ways to retrieve desired information.  ...  With our syntactic and semantic features, our system achieves a Top-1 MARR of 74.11% and Top-5 MARR of 76.68%. Compared to the baseline system,  ...  We employ a linear model to calculate a candidate's score based on its features.  ... 
doi:10.1109/iri.2008.4583027 dblp:conf/iri/LinCDDTH08 fatcat:jx53mbgxpbft5emfgx2jeazpyq

External features enriched model for biomedical question answering

Gezheng Xu, Wenge Rong, Yanmeng Wang, Yuanxin Ouyang, Zhang Xiong
2021 BMC Bioinformatics  
Background Biomedical question answering (QA) is a sub-task of natural language processing in a specific domain, which aims to answer a question in the biomedical field based on one or more related passages  ...  Results Inspired by the importance of syntactic and lexical features in the biomedical corpus, we proposed a new framework to extract external features, such as part-of-speech and named-entity recognition  ...  In general, the goal of MRC based QA task is to answer a specific question given one or more related passages.  ... 
doi:10.1186/s12859-021-04176-7 pmid:34039273 fatcat:shdrzlzntbhapnmcsd2q5hwr7u
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