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  1. Proceedings of the 2006 international workshop on Research issues in digital libraries (IWRIDL '06)
  2. Finding an answer to a question
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On the science of search: statistical approaches, evaluation, optimisation
Shallow syntax analysis in Sanskrit guided by semantic nets constraints
Digital audiovisual repositories: an introduction
Digitizing, coding, annotating, disseminating, and preserving documents
Multilingual information access: the contribution of evaluation
Information retrieval and digital libraries: lessons of research
Vagueness and uncertainty in information retrieval: how can fuzzy sets help?
Finding an answer to a question
Diffusion maps-based image clustering
Document image analysis for digital libraries
From CLIR to CLIE: some lessons in NTCIR evaluation
How the dragons work: searching in a web
Toward a common semantics between media and languages
How to compose a complex document recognition system
Advances in XML retrieval: the INEX initiative
Open source search and research

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Finding an answer to a question

Content Provider ACM Digital Library
Author Grau, Brigitte
Abstract The huge quantity of available electronic information leads to a growing need for users to have tools able to be precise and selective. These kinds of tools have to provide answers to requests quite rapidly without requiring the user to explore each document, to reformulate her request or to seek for the answer inside documents. From that viewpoint, finding an answer consists not only in finding relevant documents but also in extracting relevant parts. This leads us to express the question-answering problem in terms of an information retrieval problem that can be solved using natural language processing (NLP) approaches. In my talk, I will focus on defining what a "good" answer is, and how a system can find it. A good answer has to give the required piece of information. However, it is not sufficient; it also has both to be presented within its context of interpretation and to be justified in order to give a user means to evaluate if the answer fits her needs and is appropriate. One can view searching an answer to a question as a reformulation problem: according to what is asked, find one of the different linguistic expressions of the answer in all candidate sentences. Within this framework, interlingual question-answering can also be seen as another kind of linguistic variation. The answer phrasing can be considered as an affirmative reformulation of the question, partly or totally, which entails the definition of models that match with sentences containing the answer. According to the different approaches, the kinds of model and the matching criteria greatly differ. It can consist in building a structured representation that makes explicit the semantic relations between the concepts of the question and that is compared to a similar representation of sentences. As this approach requires a syntactic parser and a semantic knowledge base, which are not always available in all the languages, systems often apply a less formal approach based on a similarity measure between a passage and the question and answers are extracted from highest scored passages. Similarity involves different criteria: question terms and their linguistic variations in passages, syntactic proximity, answer type. We will see that, in such an approach, justifications can be envisioned by using text themselves, considered as depositories of semantic knowledge. I will focus on the approach the LIR group of LIMSI has taken for its monolingual and bilingual systems.
Starting Page 1
Ending Page 7
Page Count 7
File Format PDF
ISBN 1595936084
DOI 10.1145/1364742.1364751
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2006-12-12
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Computational linguistic Passage retrieval Natural language processing Question answering Answer extraction
Content Type Text
Resource Type Article
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