Lin, C-Y. 1999. Training a selection function for extraction. Proceedings of the the Eighteenth International Conference on Information and Knowledge Management (CIKM'99), pp. 1-8. Home/Search Document Details and Download
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Summarization Evaluation: An Overview - Mani (2001) (2 citations) (Correct)
....that measured the overlap between summaries and answers in the answer key using four different Content based vocabulary overlap measures. The correlation between the summary participants scores on each of the four overlap measures and each of the scores assigned by the human was very strong. [15] and [18] have reused the SUMMAC Q A data along with automatic scoring. 3 Extrinsic Methods 3.1 Introduction The idea of an extrinsic summarization evaluation is to determine the effect of summarization on some other task. A variety of different tasks can be considered: If the summary ....
Lin, C-Y. 1999. Training a selection function for extraction. Proceedings of the the Eighteenth International Conference on Information and Knowledge Management (CIKM'99), pp. 1-8.
A Summarization System With Categorization of Document.. - Nobata, Sekine.. (Correct)
.... summarization, Sentence extraction, Document set categorization, Sentence similarity 1 Introduction Our summarization system is based on a system that we developed for TSC2001[7] and uses a sentenceextraction technique, a frequently used method for summarization ( 9] 2] 12] 8] 1] [4]) Since our previous system could only produce a summary for a single document, we added two modules so that we could apply the system to a multi document summarization task. One module is to categorize document sets to allow multi document summarization, and the other is to estimate the ....
C.-Y. Lin. Training a selection function for extraction. In Proc. of the CIKM'99, 1999.
Sentence Extraction with Information Extraction technique - Sekine, Nobata (Correct)
....a method of integrating several clues to extract sentences. He manually assigned parameter values to integrate evidence for estimating the signi cance score of sentences. On the other hand, machine learning methods can be applicable to integrate clues. Aone et al. 1] use Bayes rule, and Lin [4] and Nomoto Matsumoto [5] generate a decision tree [6] for sentence extraction from training data. We integrated IE technique into our summarization system based on sentence extraction, which has performed one of the best results in the Text Summarization Challenge (TSC) the evaluation ....
Chin-Yew Lin. Training a selection function for extraction. In Proc. of the CIKM'99, 1999.
Machine Translation for Information Access across the . . . - Lin (1999) (Correct)
....identification stage is by far the most developed; in fact, the production version of SUMMARIST presently produces extracts only. SUMMARIST is capable of generating query biased summaries that reflect both users concerns and the main ideas of the respective documents through automated training [15]. Uses can also specify length of summaries. The inclusion of a summarization engine not only boosts the performance of user relevance judgements, but also eliminates the cost of translating unnecessary information. As shown in Figure 1, users can choose to submit only summaries instead of full ....
....button to see more translation lexical alternatives. We have deployed a beta version of MuST at ISI and demonstrated the system in several conferences. Although the initial feedback from our users is positive and detailed evaluations of some modules such as the summarization engine are available [15], we plan to perform more user studies in the future. 4 Conclusions and Future Directions In this paper we describe the design and implementation of MuST, a multilingual information retrieval, summarization, and translation system. MuST emphasizes enabling users to perform crosslanguage ....
Lin, C. Y. Training a Selection Function for Extraction. Submitted.
Query-Relevant Summarization using FAQs - Berger, Mittal (2000) (3 citations) (Correct)
No context found.
Chin-Yew Lin. 1999. Training a selection function for extraction. In Proc. of the Eighth ACM Conf. on Info. and Knowledge Mgmt (CIKM-99), Kansas City, MO.
Query-Relevant Summarization using FAQs - Berger, Mittal (2000) (3 citations) (Correct)
No context found.
Chin-Yew Lin. 1999. Training a selection function for extraction. In Proc. of the Eighth ACM Conf. on Info. and Knowledge Mgmt (CIKM-99), Kansas City, MO.
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