This paper describes the work for our participation in the NTCIR-5 Chinese to Chinese Question Answering task. Our strategy is based on the “Retrieval plus Extraction” approach. We first retrieve relevant documents, then retrieve short passages from the above documents, and finally extract named entity answers from the most relevant passages. For question type identification, we use simple heuristic rules which can cover most questions. The Lemur toolkit with the OKAPI model is used for document retrieval. Results of our task submission are given and some preliminary conclusions drawn
The DLT Group took part in the CLQA task for Chinese. With a basic system we achieved 14% overall
This paper describes our Complex Cross-Lingual Question Answering (CCLQA) system based on the techno...
We participated in the Chinese single language information retrieval(SLIR) C-C task and English-Chin...
This paper describes the work for our participation in the NTCIR-5 Chinese to Chinese Question Answe...
This paper describes the work for our participation in the NTCIR-5 Chinese to Chinese Question Answe...
This paper describes details of our participation in the NTCIR-6 Chinese-to-Chinese Question Answer...
This paper describes details of our participation in the NTCIR-6 Chinese-to-Chinese Question Answeri...
We continue to employ a minimal approach for our Chinese QA work that requires only a COTS entity ex...
We participated in the English-Chinese CLQA task with the following procedures. An English question ...
This paper describes our participation in the NTCIR-5 CLQA task. Three runs were officially submitte...
An important element in question answering systems is the analysis and interpretation of questions. ...
This paper describes our work on the subtask of simplified Chinese monolingual information retrieval...
Question-answering (QA) is a next-generation search technology which aims to provide answers to a us...
We describe DCU's participation in the NTCIR-8 IR4QA task [16]. This task is a cross-language infor...
In this paper we discuss our results from the 2006 NTCIR-6 CLQA task, subtasks 2a and 2b. We describ...
The DLT Group took part in the CLQA task for Chinese. With a basic system we achieved 14% overall
This paper describes our Complex Cross-Lingual Question Answering (CCLQA) system based on the techno...
We participated in the Chinese single language information retrieval(SLIR) C-C task and English-Chin...
This paper describes the work for our participation in the NTCIR-5 Chinese to Chinese Question Answe...
This paper describes the work for our participation in the NTCIR-5 Chinese to Chinese Question Answe...
This paper describes details of our participation in the NTCIR-6 Chinese-to-Chinese Question Answer...
This paper describes details of our participation in the NTCIR-6 Chinese-to-Chinese Question Answeri...
We continue to employ a minimal approach for our Chinese QA work that requires only a COTS entity ex...
We participated in the English-Chinese CLQA task with the following procedures. An English question ...
This paper describes our participation in the NTCIR-5 CLQA task. Three runs were officially submitte...
An important element in question answering systems is the analysis and interpretation of questions. ...
This paper describes our work on the subtask of simplified Chinese monolingual information retrieval...
Question-answering (QA) is a next-generation search technology which aims to provide answers to a us...
We describe DCU's participation in the NTCIR-8 IR4QA task [16]. This task is a cross-language infor...
In this paper we discuss our results from the 2006 NTCIR-6 CLQA task, subtasks 2a and 2b. We describ...
The DLT Group took part in the CLQA task for Chinese. With a basic system we achieved 14% overall
This paper describes our Complex Cross-Lingual Question Answering (CCLQA) system based on the techno...
We participated in the Chinese single language information retrieval(SLIR) C-C task and English-Chin...