UPM Institutional Repository

Semantically factoid question answering using fuzzy SVM named entity recognition


Mansouri, Alireza and Affendey, Lilly Suriani and Mamat, Ali and Abdul Kadir, Rabiah (2008) Semantically factoid question answering using fuzzy SVM named entity recognition. In: 3rd International Symposium on Information Technology (ITSim'08), 26-28 Aug. 2008, Kuala Lumpur, Malaysia. .


Named Entity Recognition (NER) and Question Answering (QA) are fundamental tasks and they are the cores of natural language processing (NLP) system. NER, a sub problem of Information Extraction (IE), involves recognizing and extracting name entities like Persons, Locations, Organizations, Dates and Times from electronics resources and text. Question Answering (QA) is a type of Information Retrieval (IR), attempts to deal with a wide range of question. In this paper we propose a semantically Factoid Question Answering model using Fuzzy Support Vector Machine Named Entity Recognizer component called FSVM. In this model we applied the FSVM NE recognizer to filter Question Answering system results have token by IR and return exact expect result to the user. This paper shows how the Fuzzy NER can applied in information retrieval (IR) systems in applications like Question Answering (QA). We show a model to improve precision in QA by semantically NER and reducing Answer Finder input data.

Download File

Text (Abstract)
Semantically factoid question answering using fuzzy SVM named entity recognition.pdf

Download (34kB) | Preview

Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.1109/ITSIM.2008.4631684
Publisher: IEEE
Keywords: Question Answering (QA); Named Entity Recognition (NER); Information extraction
Depositing User: Nabilah Mustapa
Date Deposited: 11 Jun 2019 01:41
Last Modified: 11 Jun 2019 01:41
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ITSIM.2008.4631684
URI: http://psasir.upm.edu.my/id/eprint/68864
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item