A maximum entropy approach to natural language processing
Computational Linguistics
High performance question/answering
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Noun phrase recognition by system combination
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
SVM answer selection for open-domain question answering
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Using machine learning techniques to interpret WH-questions
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Question answering using maximum entropy components
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
A noisy-channel approach to question answering
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Question classification using HDAG kernel
MultiSumQA '03 Proceedings of the ACL 2003 workshop on Multilingual summarization and question answering - Volume 12
A knowledge based method for the medical question answering problem
Computers in Biology and Medicine
A machine learning approach for Indonesian question answering system
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Linguistic kernels for answer re-ranking in question answering systems
Information Processing and Management: an International Journal
Applying NLP techniques and biomedical resources to medical questions in QA performance
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Language independent answer prediction from the web
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
A maximum entropy model based answer extraction for chinese question answering
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Molecular sequence alignment for extracting answers for where-typed questions from google snippets
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Using syntactic and semantic structural kernels for classifying definition questions in Jeopardy!
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Structural relationships for large-scale learning of answer re-ranking
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
A support vector machine-based context-ranking model for question answering
Information Sciences: an International Journal
Answer extraction from passage graph for question answering
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
| Hi-index | 0.00 |
This paper regards Question Answering (QA) as Question-Biased Term Extraction (QBTE). This new QBTE approach liberates QA systems from the heavy burden imposed by question types (or answer types). In conventional approaches, a QA system analyzes a given question and determines the question type, and then it selects answers from among answer candidates that match the question type. Consequently, the output of a QA system is restricted by the design of the question types. The QBTE directly extracts answers as terms biased by the question. To confirm the feasibility of our QBTE approach, we conducted experiments on the CRL QA Data based on 10-fold cross validation, using Maximum Entropy Models (MEMs) as an ML technique. Experimental results showed that the trained system achieved 0.36 in MRR and 0.47 in Top5 accuracy.