B. Baldwin and T. S. Morton. Dynamic coreference-based summarization. In Proceedings of the Third Conference on Empirical Methods in Natural Language Processing (EMNLP-3), Granada, Spanien, June 1998.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....from the original text for the summary based on characteristic words [10] Such words and ways to find them are of special interest here. One approach is to use lexical knowledge from sources such as WORDNET [11] compare [2] Another is to use statistical information gathered from a corpus [1]. A well known measure that relies only on the given text collection is Tf Idf (used, for example, in [3, 4] which measures how characteristic a word is for its text. Considering domain specific summarization, words that are characteristic for a given topic, not for a text as a whole, must be ....

....how characteristic a word is for its text. Considering domain specific summarization, words that are characteristic for a given topic, not for a text as a whole, must be found. In the context of Information Retrieval, words from the user query indicate the topic for specific summarization [13, 1], but only coarsely as queries tend to be rather short. Sentence compression has only recently been explored. In most approaches, syntactical clues were used to find phrases within a sentence that can be cancelled [7, 9] However, as will be argued in section 4.2, important information can show ....

B. Baldwin and T. S. Morton. Dynamic coreference-based summarization. In Proceedings of the Third Conference on Empirical Methods in Natural Language Processing (EMNLP-3), Granada, Spanien, June 1998.

....automated document summarization bytext span extraction dates back at least to Luhn s work at IBM in the fifties [12] Most of the work in sentence extraction applied statistical techniques (frequency analysis, variance analysis, etc. to linguistic units suchastokens, names, anaphora, etc. e.g. [27, 19, 9, 18, 2]. Other approaches include the utility of discourse structure [14] the combination of information extraction and language generation [11, 17, 24, 21, 16] and using machine learning to find patterns in text [28, 4, 26] Several researchers have extended various aspects of the single document ....

Breck Baldwin and Thomas S. Morton. Dynamic coreference-based summarization. In Proceedings of the ThirdConference on Empirical Methods in Natural Language Processing (EMNLP-3), Granada, Spain, 171 June 1998.

....problem through the seventies and eighties (e.g. 17, 25] The resources devoted to addressing this problem grew by several orders of magnitude with the advent of the world wide web and large scale search engines. Several innovative approaches began to be explored: linguistic approaches (e.g. [1, 2, 4, 12,14,15, 18]) statistical and information centric approaches (e.g. 6, 9, 16, 24] and combinations of the two (e.g. 3, 24,26] The TIPSTER Phase III Program, an information retrieval initiative of the US Defense Department funded several of these projects on summarization [27] Almost all of this work ....

Baldwin, B., and Morton, T. S. Dynamic coreferencebased summarization. In Proceedings of the Third Conference on Empirical Methods in Natural Language Processing (EMNLP-3) (Granada, Spain, June 1998).

....we have implemented and preliminarily evaluated, could easily be extended to allow summaries to be generated from (parts of) the best n coreference chains, or from event, as well as object, coreference chains. The use of document extracts formed from coreference chains is not novel. Bagga and Baldwin (1998) describe a technique for crossdocument coreference which involves extracting the set of all sentences containing expressions in a coreference chain for a specific entity (e.g. John Smith) from each of several documents. They then employ a thresholded vector space similarity measure between these ....

....expressions in a coreference chain for a specific entity (e.g. John Smith) from each of several documents. They then employ a thresholded vector space similarity measure between these document extracts to decide whether the documents are discussing the same entity (i.e. the same John Smith) Baldwin and Morton (1998) describe a query sensitive (i.e. user focused) summarization technique that involves extracting sentences from a document which contain phrases that corefer with expressions in the query. The resulting extract is used to support relevancy judgments with respect to the query. The use of chains of ....

[Article contains additional citation context not shown here]

B. Baldwin and T.S. Morton. 1998. Dynamic coreference-based summarization. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP'98).

.... to the user query [9, 31, 32, 42] Some systems include sub document relevance assessments and convey this information to the user via techniques such as text tiling [15] More recently, single document summarization systems provide an automated generic abstract or a query relevant summary [3, 4, 6, 8, 10, 16, 19, 20, 25, 27, 29, 30, 35 38]. Such a summary minimally provides an indication of the information content of a document so that a user can choose whether or not to read it. A more effective ideal summary will contain the content for which the user is searching. However, large scale IR and summarization have not yet been ....

....a text span in the summary, and retrieve original document(s) for further information. Thus a user interface which supports these functions is a key component. 4. The co reference problem in summarization presents even greater challenges for multi document than for single document summarization [4]. For example, a multi document summary may contain text spans from several documents. If a text span in the summary contains a pronoun and not its preceding referent, it is most likely to given a false indication (association with a prior referent to which it is not linked) or leave the reader ....

[Article contains additional citation context not shown here]

B. Baldwin and T. S. Morton. Dynamic coreference-based summarization. In Proceedings of the Third Conference on Empirical Methods in Natural Language Processing (EMNLP-3), Granada, Spain, June 1998.

....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 ....

Baldwin, B., and Morton, T. S. Dynamic coreferencebased summarization. In Proceedings of the Third Conference on Empirical Methods in Natural Language Processing (EMNLP-3) (Granada, Spain, June 1998).

....remains can be deemed a summary of the original document. Most of the previous work on extraction based summarization is based on the use of statistical techniques such as frequency or variance analysis applied to linguistic units such as tokens, names, anaphoric or co reference information (e.g. (Baldwin Morton 1998; Boguraev Kennedy 1997; Aone et al. 1997; Carbonell Goldstein 1998; Hovy Lin 1997; Mitra, Singhal, Buckley 1997) More involved approaches have attempted to use discourse Copyright c 1999, American Association of Artificial Intelligence (www.aaai.org) All rights reserved. structure ....

Baldwin, B., and Morton, T. S. 1998. Dynamic coreference-based summarization. In Proceedings of EMNLP-3 Conference.

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