Designing an interactive open-domain question answering system

Quarteroni, Silvia; Manandhar, Suresh

doi:10.1017/s1351324908004919

Cited by 73 publications

(39 citation statements)

References 28 publications

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“…This support can be obtained from experience staff or programmers, and other document from Yahoo answer. Before building the system the above consideration are taken into account for developing the proposed system [1]. Along with the improvement of underlying communication technology, community QA has emerged as an extremely popular alternative to acquire information online, information gainer are able to post their specific question on any topic and obtain answer provided by other participants.…”

Section: Litrature Surveymentioning

confidence: 99%

Information Searching Using Web Data Extraction for Acquiring Enrich MM Results

Firoz¹

2015

IJRITCC

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Abstract-There are many question answer sites are available now a day. In that Community Question Answering Sites are achieved lots of popularity over last years. But the drawback of available question answering system is that it can only provide multiple solutions of the textual answer and user need to select one of them. In this paper, we propose a scheme that enriches the textual answer with multimedia data. Our scheme consists of four models: QA pair extraction, answer medium selection, query generation and selection and presentation. The type media information added with the textual data is determined. The question answer pair is generated from the available Community Question Answering Sites database. Query is generated for the multimedia data. The final resulting data must be selected after re-ranking and removal operation and then present to the user.

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Section: Litrature Surveymentioning

confidence: 99%

Information Searching Using Web Data Extraction for Acquiring Enrich MM Results

Firoz¹

2015

IJRITCC

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“…In the late 1990s QA track in TREC [6] gain popularity in Text based QA. Based on the question and the expected answer, we classify QA into Open Domain QA [7], Restricted Domain QA [8], Definition QA [9] and Listed QA [10].Cqa is an alternative approach. It is a large and diverse question answer forum, which share technical knowledge as well as advices and opinion.…”

Section: Related Workmentioning

confidence: 99%

Advanced Community Question Answering Sites with Multimedia Answers

Sekhar¹,

S.T²,

Kumar³

2014

IJETT

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There are many question answer sites are available now a days. Community question answering sites are efficient when compare with the automate question answering sites. The drawback of available community question answering system is that it can only provide textual answer. In this paper, we propose a scheme that enriches the textual answer with multimedia data. Our scheme consists of four components: natural language processing, qa pair extraction, query generation, multimedia data selection and presentation. The question answer pair is extracted from the available community question answering sites database by online. Query is generated for the multimedia data. The resulting data is selected and present to the user.

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“…Lars et al [24] argue that the discourse structure in natural language interfaces is, given the limited set of actions to be performed by the system and the user, simpler than the one underlying human-human dialog. Quarteroni and Manandhar [25] introduce an open-domain question answering system named YourQA where queries can be posed in a dialog [26] with the system. They add an additional user mode module, keeping track of the user's age range, reading level, and web pages of interest [27], and they employed a dialog manager to make the system intelligently interact with the user which first identifies the user query's speech act and then resolves the different contextual references by different strategies.…”

Section: Discourse Modelingmentioning

confidence: 99%

Answering contextual questions based on ontologies and question templates

Wang

2011

Front. Comput. Sci. China

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Contextual question answering (CQA), in which user information needs are satisfied through an interactive question answering (QA) dialog, has recently attracted more research attention. One challenge is to fuse contextual information into the understanding process of relevant questions. In this paper, a discourse structure is proposed to maintain semantic information, and approaches for recognition of relevancy type and fusion of contextual information according to relevancy type are proposed. The system is evaluated on real contextual QA data. The results show that better performance is achieved than a baseline system and almost the same performance as when these contextual phenomena are resolved manually. A detailed evaluation analysis is presented.

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Designing an interactive open-domain question answering system

Cited by 73 publications

References 28 publications

Information Searching Using Web Data Extraction for Acquiring Enrich MM Results

Information Searching Using Web Data Extraction for Acquiring Enrich MM Results

Advanced Community Question Answering Sites with Multimedia Answers

Answering contextual questions based on ontologies and question templates

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