V. Mittal, M. Kantrowitz, J. Goldstein, J. Carbonell. Selecting text spans for document summaries: Heuristics and metrics. In Proceedings of the National Conference on Artificial Intelligence, pp. 467-473, 1999. Home/Search Document Details and Download
Summary Related Articles Check |
This paper is cited in the following contexts:
A Comparison of Summarization Methods Based on Task-based.. - Mochizuki, OKUMURA (Correct)
.... of documents relevant to the query higher than 50 because a smaller number of relevant documents would make the results of the 1 We admit that we should make more thorough experiments with multiple summary lengths, since different summary lengths will yield different results(Jing et al. 1998; Mittal et al. 1999). 2 BMIR J2 was constructed by the SIG Database Systems of the Information Processing Society of Japan, in collaboration with the Real World Computing Partnership. experiments less reliable. The average length of the queries is 3.2 words, and the average length of the documents is 1,323.3 ....
Mittal, V., M. Kantrowitz, J. Goldstein, and J. Carbonell, 1999. Selecting text spans for document summaries: Heuristics and metrics. In Proc. of the 16th National Conference on Artificial Intelligence. pages 467--473.
Automatic Text Summarization of Multiple Documents - Goldstein (1999) (2 citations) Self-citation (Goldstein) (Correct)
....by how well they perform on certain (extrinsic tasks [23] indicating document relevance to a topic, indicating a category for the document or intrinsic tasks whether they contain answers to specific questions. Summaries can also be evaluated by whether they extract the relevant portions of text [13,28] (intrinsic) which is the focus of my research. 2.2 Multi Document In the past few years, multi document summarization has become a subject of great interest due to the rapid increase in textual information, which has made it virtually impossible for users to browse or read many individual ....
....such as who and where, linguistic features such as name and place could be boosted in the weighting. CMU and GE used these features for the Q A section of the TIPSTER formal evaluation with some success [39] Other linguistic features include quotations, honorifics, and thematic phrases [28]. Furthermore, different document genres can be assigned weights to reflect their individual linguistic features, a method used by GE [36] For example, it is a well known fact that summaries of newswire stories usually include the first sentence of the article (see Table 1) Accordingly, this ....
[Article contains additional citation context not shown here]
V. O. Mittal, M. Kantrowitz, J. Goldstein, and J. Carbonell. Selecting Text Spans for Document Summaries: Heuristics and Metrics. In Proceedings of AAAI-99, Orlando, FL, July 1999.
Summarizing Text Documents: Sentence Selection and Evaluation.. - Goldstein (1999) (17 citations) Self-citation (Mittal Kantrowitz Goldstein Carbonell) (Correct)
....problem through the seventies and eighties (e.g. 19, 26] The resources devoted to addressing this problem grew by several orders of magnitude with the advent of the worldwide web and large scale search engines. Several innovative approaches began to be explored: linguistic approaches (e.g. [2, 3, 6, 12, 15, 16, 18, 20]) statistical and informationcentric approaches (e.g. 8, 9, 17, 25] and combinations of the two (e.g. 5, 25] Almost all of this work (with the exception of [12,16,20,24] focused on summarization by text span extraction , with sentences as the most common type of text span. This ....
....linguistic features such as name and place could be boosted in the weighting. CMU and GE used these features for the Q A section of the TIPSTER formal evaluation with some success [14] Other linguistic features include quotations, honorifics, and thematic phrases, as discussed in Section 4 [18]. Furthermore, different document genres can be assigned weights to reflect their individual linguistic features, a method used by GE [25] For example, it is a well known fact that summaries of newswire stories usually include the first sentence of the article (see Table 1) Accordingly, this ....
Mittal, V. O., Kantrowitz, M., Goldstein, J., and Carbonell, J. Selecting Text Spans for DocumentSummaries: Heuristics and Metrics. In Proceedings of AAAI-99 (Orlando, FL, July 1999).
Applications of Lexical Cohesion in the Topic Detection and.. - Stokes (2004) (Correct)
No context found.
V. Mittal, M. Kantrowitz, J. Goldstein, J. Carbonell. Selecting text spans for document summaries: Heuristics and metrics. In Proceedings of the National Conference on Artificial Intelligence, pp. 467-473, 1999.
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC