M. Sanderson and B. W. Croft. Deriving Concept Hierarchies from Text. In Proceedings of the 22nd ACM SIGIR, pages 206--213, 1999.  Home/Search Document Details and Download
Summary Related Articles Check |
This paper is cited in the following contexts:
First 50 documents
Entity Models: Construction and Applications - Allan, Raghavan (Correct)
....of the form Tennis Graf, that is, where the links are not just between entities but also include classes of entities (as in the previous section) Once this is obtained it can used to build a taxonomy of people, places and, organizations. This can then be used as a topic or concept hierarchy [20] or like the Yahoo hierarchies. This is thus a start to using language modeling to generate hierarchies and association graphs. The problem of finding relationships between items is a typical text mining challenge [7, 10, 13] though co occurrence techniques and or careful natural language ....
M. Sanderson and W. B. Croft. Deriving concept hierarchies from text. In Research and Development in Information Retrieval, pages 206--213, 1999.
CVS: A Correlation-Verification Based Smoothing Technique on.. - Chung, Chen (Correct)
....These methods do not consider the correlation of term pairs in light of the relationship with other term pairs in the corpus. Our approach augments these methods by selecting better terms for query expansion by clustering. As opposed to document clustering ( 9, 19] we consider term clustering ([22, 15, 23, 3]) Term clustering groups related terms into a hierarchy of clusters by minimizing intra cluster distances and maximizing intercluster distances. User queries are expanded by terms in the clusters that contain the terms in the query. A hierarchy of clusters gives a user guidance in adjusting the ....
M. Sanderson and B. Croft. Deriving concept hierarchies from text. In International Conference on Research and Development in Information Retrieval (SIGIR 1999.
Using Part-of-speech Patterns to Reduce Query Ambiguity - Allan, Raghavan (Correct)
....are focusing on that situation in this study. There is a range of information retrieval interface ideas that attempt to help the user deal with ambiguous queries. Sanderson, Lawrie, and Croft have been working on concept hierarchies that provide a hierarchical map of words and their relationships [19, 21, 11, 17]. A user can navigate the hierarchy to find the sense that is relevant. To date that research has not directly investigated whether the hierarchies help with disambiguation, looking instead at their ability to a#ect recall and precision. Clustering the retrieved document set is another way to ....
Mark Sanderson and W. Bruce Croft. Deriving concept hierarchies from text. In Proceedings of the ACM Conference on Research in Information Retrieval (SIGIR), pages 206--213, 1999.
Inferring Hierarchical Descriptions - Glover, Pennock, Lawrence, Krovetz (2002) (2 citations) (Correct)
....do not necessarily relate to the actual frequency of the concepts in the set. Given a cluster of sports documents that discusses primarily basketball and hockey, the fact that baseball is also a sport is not as important for describing that set as other relationships. Sanderson and Croft [10] presented a statistical technique based on subsumption relations. In their model, for two terms x and y, x is said to subsume y if the probability of x given y is one, and the probability of y given x is less than one. A subsumption relationship is suggestive of a parentchild relationship (in ....
Mark Sanderson and Bruce Croft. Deriving concept hierarchies from text. In 22nd ACM SIGIR Conference, pages 206--213, 1999.
A Study of User Interaction with a Concept-based.. - Joho, Sanderson.. Self-citation (Sanderson) (Correct)
No context found.
Sanderson, M., Croft, B.: Deriving concept hierarchies from text. In Hearst, M., Gey, G., Tong, R., eds.: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Berkeley, CA, ACM (1999) 206--213
Language Models for Hierarchical Summarization - Lawrie (2003) (1 citation) Self-citation (Croft) (Correct)
No context found.
Sanderson, M., and Croft, W. B. Deriving concept hierarchies from text. In Proceedings of the 22nd annual international ACM SIGIR conference on Research and Development in Information Retrieval (1999), pp. 206--213.
Generating Hierarchical Summaries for Web Searches - Lawrie, Croft (2003) (1 citation) Self-citation (Croft) (Correct)
....the set of vocabulary terms V , AT is the function AT : V # 0, 1 where: AT (w) 1 if the word w is in T (the set of topical terms) The second quality is predictiveness. Predictive terms are those whose occurrence is a precondition for many other terms. Previous work on topic hierarchies[9, 10, 18] has shown that this is an important aspect of topic terms, because these are the terms that are frequently used to discuss the topic at different levels of generality. Apple Boost AirPort Security . ISP November 13, 2001 Apple Boost AirPort Security, Features By Jim Wagner Software ....
....By definition, a hierarchy should have general terms at the high levels and become more specific at lower levels. This restriction is not enforced by combining the qualities of topicality and predictiveness. However, the frequency of a term is a good indication of generality or specificity[18]. This means that lower level terms should be less frequent than their parents. Aside from enforcing a quality that should be present in the hierarchy, this restriction also limits the number of terms that will be considered at a given level of the hierarchy, improving the efficiency of the ....
[Article contains additional citation context not shown here]
M. Sanderson and W. B. Croft. Deriving concept hierarchies from text. In Proceedings of the 22nd annual international ACM SIGIR conference on Research and Development in Information Retrieval, pages 206--213, 1999.
Building Automatically a Business Registration Ontology - Melania Degeratu Vasileios (2002) (1 citation) (Correct)
No context found.
M. Sanderson and B. W. Croft. Deriving Concept Hierarchies from Text. In Proceedings of the 22nd ACM SIGIR, pages 206--213, 1999.
Learning Taxonomic Relations from Heterogeneous.. - Cimiano, Pivk.. (2003) (5 citations) (Correct)
No context found.
M. Sanderson and B. Croft. Deriving concept hierarchies from text. In Research and Development in Information Retrieval, pages 206--213. 1999.
A User Evaluation of Hierarchical Phrase Browsing - Katrina Edgar David (2003) (Correct)
No context found.
Sanderson, M. Croft, W. B.: Deriving Concept Hierarchies from Text. In Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Berkeley, CA, USA (1999) 206-213.
Automatic Generation of Web Portals Using Artificial Ants - Hanene Azzag Polytech (2005) (Correct)
No context found.
M. Sanderson and W. B. Croft. Deriving concept hierarchies from text. In Research and Development in Information Retrieval, pages 206--213, 1999.
Query Modification by Discovering Topics from - Web Page Structures (2004) (Correct)
No context found.
Mark Sanderson and Bruce Croft. Deriving concept hierarchies from text. In Proceedings of the 22nd ACM SIGIR Conference (SIGIR'99), pages 206--213, 1999.
Emergent Semantics Principles and Issues - Karl Aberer Philippe (Correct)
No context found.
M. Sanderson and B. Croft. Deriving concept hierarchies from text. In Research and Development in Information Retrieval, pages 206--213. 1999.
An Improved Method for Image Retrieval Using Speech.. - Chen, Tan, Mulhem.. (2003) (Correct)
No context found.
M. Sanderson, B. Croft, Deriving Concept Hierarchies from Text, SIGIR '99, 206-213, 1999.
LiveClassifier: Creating Hierarchical Text Classifiers.. - Huang, Chuang, Chien (2004) (1 citation) (Correct)
No context found.
M. Sanderson and W. B. Croft. Deriving concept hierarchies from text. In Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 206--213, 1999.
A Hierarchical Monothetic Document Clustering Algorithm - And (2004) (Correct)
No context found.
M. Sanderson and W.B.Croft. Deriving concept hierarchies from text. In Proceedings of SIGIR, pages 206--213, 1999.
IT Licentiate theses - Bootstrapping And Decentralizing (2003) (Correct)
No context found.
M. Sanderson and W. B. Croft. Deriving concept hierarchies from text. In Research and Development in Information Retrieval, pages 206--213, 1999.
Deriving Concept Hierarchies from Text by Smooth Formal.. - Cimiano, Staab, Tane (2003) (Correct)
No context found.
M. Sanderson and B. Croft. Deriving concept hierarchies from text. In Research and Development in Information Retrieval, pages 206--213. 1999.
Implementing Document Ranking within a Logical Framework - David Losada Ailab (2000) (Correct)
No context found.
M. Sanderson and B. Croft. Deriving concept hierarchies from text. In Proc. of SIGIR-99, the 22nd ACM Conference on Research and Development in Information Retrieval, pages 206--213, Berkeley, August 1999.
A User Evaluation of Hierarchical Phrase Browsing - Katrina Edgar David (Correct)
No context found.
Sanderson, M. Croft, W. B.: Deriving Concept Hierarchies from Text. In Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Berkeley, CA, USA (1999) 206-213.
Automatically Acquired Domain Knowledge for Ad Hoc Search.. - Kruschwitz (2003) (Correct)
No context found.
SANDERSON, M., AND CROFT, B. Deriving concept hierarchies from text. In Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (Berkeley, CA, 1999), pp. 206-- 213.
Emergent Semantics Principles and Issues - Aberer, Cudré-Mauroux.. (2004) (Correct)
No context found.
M. Sanderson and B. Croft. Deriving concept hierarchies from text. In Research and Development in Information Retrieval, pages 206--213. 1999.
Using Speech Annotation for Home Digital Image Indexing and.. - Chen, Tan, Mulhem (2003) (Correct)
No context found.
M. Sanderson, B. Croft, Deriving Concept Hierarchies from Text, SIGIR '99, 206-213, 1999.
Learning Taxonomic Relations from Heterogeneous Evidence - Cimiano, Pivk.. (2004) (5 citations) (Correct)
No context found.
M. Sanderson and B. Croft, `Deriving concept hierarchies from text', in Research and Development in Information Retrieval, 206--213, (1999).
Improving Document Retrieval by Automatic Query.. - Klink, Hust, Junker.. (2002) (4 citations) (Correct)
No context found.
Sanderson M., Croft B.: Deriving concept hierarchies from text. In Proceedings of the 22 "a Annual lnt. ACM S1G1R Conference on Research and Development in Information Retrieval, pp. 206 - 213, Berkeley, CA, August 1999
First 50 documents
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