Adapting a semantic question answering system to the web

The growth of information retrieval from the web sources are increased day by day, proving an effective and efficient way to the user for retrieving relevant documents from the web is an art. Asking the right question and retrieving a right answer to the posted query is a service which provide by the Natural Language Processing. Question Answering System is one of the best ways to identify the candidate answer with high accuracy. The web and Semantic Knowledge Driven Question Answering System (QAS) used to determine the candidate answer for the posted query in the NLP tools. This method includes Query expansion techniques and entity linking method to identify the information source snippets with ontology structure, also ranking the sentences by applying conditional probability between query and Answer to identify the optimal answer from the web corpus. The result provides an exact answer with high accuracy than the baseline method.

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Multilingual Question-Answering System in Biomedical Domain on the Web: An Evaluation

Multilingual and Multimodal Information Access Evaluation - Lecture Notes in Computer Science ◽

10.1007/978-3-642-23708-9_10 ◽

2011 ◽

pp. 83-88 ◽

Cited By ~ 8

Author(s):

María-Dolores Olvera-Lobo ◽

Juncal Gutiérrez-Artacho

Keyword(s):

Question Answering ◽

Biomedical Domain ◽

Question Answering System ◽

The Web

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Study on Finding Experts in Community Question-Answering System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.513-517.1760 ◽

2014 ◽

Vol 513-517 ◽

pp. 1760-1764 ◽

Cited By ~ 1

Author(s):

Rong Rong Yang ◽

Jian Hua Wu

Keyword(s):

Web 2.0 ◽

Web Mining ◽

Question Answering ◽

Service Model ◽

Question Answering System ◽

Community Question Answering ◽

Questions And Answers ◽

Hits Algorithm ◽

The Relationship ◽

The Web

As one of the new service model of Web 2.0, the emergence of Community Question-Answering system brings a new way for users to obtain information. However, the explosive growth of users and information, it will be hard for users to obtain the information quickly and accurately. Therefore, it is important to find experts in Community Question-Answering system to improve the accuracy and efficiency of information obtaining. This paper firstly analyzed the relationship among users, questions, and answers in Community Question-Answering system, and built the user diagram, and then by means of the Web mining technology, that is the link analysis weighted HITS algorithm, to find experts out. Finally, three evaluation indices were used to measure the validity of the experts finding algorithm. Experimental results show the effectiveness of the weighted HITS algorithm.

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