This paper describes a question answering system that automatically finds answers to questions in a large collection of documents. The prototype CNLP question answering system was developed for participation in the TREC-9 question answering track. The system uses a two-stage retrieval approach to answer finding based on keyword and named entity matching. Results indicate that the system ranks correct answers high (mostly rank 1), provided that an answer to the question was found. Performance figures and further analyses are included
The problem of efficiently finding answers to natural language questions over the web has gained muc...
The importance of Question Answering is growing with the expansion of information and text documents...
This article provides a comprehensive and comparative overview of question answering technology. It ...
This paper describes a question answering system that automatically finds answers to questions in a ...
This paper describes a question answering system that automatically finds answers to questions in a ...
This paper describes the retrieval experiments for the main task and list task of the TREC-10 questi...
This paper describes the retrieval experiments for the main task and list task of the TREC-2002 ques...
This paper describes the retrieval experiments for the main task and list task of the TREC-10 questi...
This paper describes the architecture, operation and results obtained with the Question Answering pr...
We present a question answering system with a hybrid design, combining techniques from knowledge rep...
Answering open-domain factual questions requires Natural Language processing for refining document s...
International audienceAnswering precise questions requires applying Natural Language techniques in o...
We present a question answering system that combines information at the lexical, syntactic, and sema...
In TREC 2007, Language Computer Corporation ex-plored how a new, semantically-rich framework for in-...
This paper describes the processing details and TREC-9 question answering results for our QA system....
The problem of efficiently finding answers to natural language questions over the web has gained muc...
The importance of Question Answering is growing with the expansion of information and text documents...
This article provides a comprehensive and comparative overview of question answering technology. It ...
This paper describes a question answering system that automatically finds answers to questions in a ...
This paper describes a question answering system that automatically finds answers to questions in a ...
This paper describes the retrieval experiments for the main task and list task of the TREC-10 questi...
This paper describes the retrieval experiments for the main task and list task of the TREC-2002 ques...
This paper describes the retrieval experiments for the main task and list task of the TREC-10 questi...
This paper describes the architecture, operation and results obtained with the Question Answering pr...
We present a question answering system with a hybrid design, combining techniques from knowledge rep...
Answering open-domain factual questions requires Natural Language processing for refining document s...
International audienceAnswering precise questions requires applying Natural Language techniques in o...
We present a question answering system that combines information at the lexical, syntactic, and sema...
In TREC 2007, Language Computer Corporation ex-plored how a new, semantically-rich framework for in-...
This paper describes the processing details and TREC-9 question answering results for our QA system....
The problem of efficiently finding answers to natural language questions over the web has gained muc...
The importance of Question Answering is growing with the expansion of information and text documents...
This article provides a comprehensive and comparative overview of question answering technology. It ...