Adam L. Berger and Vibhu O. Mittal. 2000. OCELOT: a system for summarizing web pages. In Research and Development in Information Retrieval, pages 144--151.  Home/Search Document Details and Download
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Optimal Mixture Models in IR - Lavrenko (2002) (1 citation) (Correct)
.... introduced by Ponte and Croft [18] and were expanded upon in a number of following publications [4, 15, 24, 8, 9, 11, 14] These approaches have proven to be very effective in a number of applications, including ad hoc retrieval [18, 4, 15] topic detection and tracking [26, 10] summarization [5], question answering [3] text segmentation [2] and other tasks. The main strength of Language Modeling techniques lies in very careful estimation of word probabilities, something that has been done in a heuristic fashion in prior research on Information Retrieval [21, 19, 20, 25] A common ....
A. Berger and V. Mittal. OCELOT: a system for summarizing web pages. In Proceedings of SIGIR, pages 144--151, 2000.
Temporal Summaries of News Topics - Allan, Gupta, Khandelwal (2001) (14 citations) (Correct)
.... sentence length and case of words [18] or compare patterns of relationships between sentences [37] Most of these approaches use statistics from the corpus itself to decide on the importance of sentences, and some leverage existing training sets of summaries to learn the properties of a summary [18, 3, 4]. Summarization techniques leverage a wide range of Natural Language Processing (NLP) and discourse information. Some focus primarily on techniques that have been developed in Information Retrieval [14] while most try to leverage both IR approaches and some aspects of NLP [16] Of course, not ....
....Of course, not all summaries are merely extracts. Some of the work already mentioned pieces together summaries from more than just sentences. Other work attempts to generate the summary directly, either from a knowledge based representation of the content or from a statistical model of the text [39, 4]. Some summarization efforts have been focused on news stories or events. Maybury s work on event data [24] is different than this work because he was focused on events from simulations or application data rather than on events within news topics. Other work on news summarization, including work ....
A. Berker and V. Mittal. OCELOT: a system for summarizing web pages. In Proceedings of SIGIR, pages 144--151, 2000.
Relevance-Based Language Models - Lavrenko, Croft (2001) (33 citations) (Correct)
....are conceptually difficult to integrate into the language modeling framework of [16] because they involve augmenting the sample (as in [15] rather than adjusting the model. Furthermore, explicit models of relevance are better suited to other information organization tasks, such as summarization [6], question answering [4] topic detection and tracking (TDT) 25, 12] and text segmentation [3] The primary obstacle to constructing effective models of relevance is the lack of training data. In a typical retrieval environment we are given a query, a large collection of documents and no ....
A. Berger and V. Mittal. OCELOT: a system for summarizing web pages. In Proceedings of SIGIR, pages 144--151, 2000.
Seeing the Whole in Parts: Text Summarization for.. - Buyukkokten.. (2000) (19 citations) (Correct)
....documents through a series of transformations and links the resulting individual pieces. Our technique is more in the tradition of Fisheye Views [12] where a large body of information is displayed in progressively greater detail, with surrounding context always visible to some extent. Ocelot [1] is a system for summarizing Web pages. Ocelot synthesizes summaries, rather than extracting representative sentences from text. The system s final result is a static summary. Ocelot does not provide progressive disclosure where users can drill into parts of the summary, as we do in the Power ....
A.L. Berger, V.O. Mittal, OCELOT: A System for Summarizing Web Pages, Proc. of 23rd Annual Conf. on Research and Development in Information Retrieval (ACM SIGIR), 2000, pp. 144-151.
Adapting Lexical Chaining to Summarize Conversational Dialogues - Iryna Gurevych Eml (2005) (Correct)
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Adam L. Berger and Vibhu O. Mittal. 2000. OCELOT: a system for summarizing web pages. In Research and Development in Information Retrieval, pages 144--151.
Evaluation of a Query-biased Document Summarisation.. - Wu, Wilkinson, Paris (2004) (Correct)
No context found.
Berger A. L. and Mittal V. O. OCELOT: A System for summarizing web pages. In Proceedings of the 23 rd ACM SIGIR Conference. July 24-28, 2000, Athens, Greece (pp. 144--151).
Web Page Summarization Using Dynamic Content - Adam Jatowt Hongo (2004) (Correct)
No context found.
Berger, A. L., and Mittal, V. O. OCELOT: a system for summarizing web pages. Proc. of the 23 rd ACM SIGIR Conference on Research and Development in Information Retrieval (Athens, Greece, July 2000), 144-151.
Combining a mixture language model and Naive Bayes for - Multi-Document.. (2001) (Correct)
No context found.
Adam L. Berger and Vibhu O. Mittal. OCELOT: a system for summarizing web pages. In Proceedings of the 23rd Annnual International ACM SIGIR Conference on research and Development in Information Retrieval, pages 144--151, 2000.
Enhanced Web Document Summarization Using Hyperlinks - Delort, Rifqi (2003) (1 citation) (Correct)
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A. L. Berger and V. O. Mittal. OCELOT: a system for summarizing Web pages. In Research and Development in Information Retrieval, pages 144--151, 2000.
Web Page Summarization Using Dynamic Content - Jatowt, Ishizuka (Correct)
No context found.
Berger, A. L., and Mittal, V. O. OCELOT: a system for summarizing web pages. Proc. of the 23 rd ACM SIGIR Conference on Research and Development in Information Retrieval (Athens, Greece, July 2000), 144-151.
Language Models for Hierarchical Summarization - Lawrie (2003) (1 citation) (Correct)
No context found.
Berger, A., and Mittal, V. OCELOT: A system for summarizing web pages. In Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval (2000), pp. 144--151.
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