Jaime Carbonell, Mark Craven, Steve Fienberg, Tom Mitchell, Yiming Yang  Home/Search
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Abstract: Moo], organization and presentation of documents in information retrieval systems [GS, Hof], collaborative filtering [dVN], lexicon learning [GBGH], query reformulation [KK], text generation [Rad] and analysis of the statistical properties of text [MA]. In short, the state of the art in learning from text and the web is that a broad range of methods are currently being applied to many important and interesting tasks. There remain numerous open research questions, however. Broadly, the goals of... (Update)
Context of citations to this paper: More
.... experiments on very short document (containing hyperlink descriptions) are described in [1, 65] Other interesting research questions [70] include the influence of sparse word statistics, the incorporation of temporal information in Web browsing behavior, a combination of...
...for mining Web log data, while [85] discusses the research issues of Web mining in the context of Web warehouse project. Carbonell et al. [20] give an overview of the workshop on learning from text and the Web that is related to Web content (from the IR view) and usage...
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BibTeX entry: (Update)
Carbonell, J., Craven, M., Fienberg, S., Mitchell, T., Yang, Y., Report on the CONALD Workshop on Learning from Text and the Web, 1998. http://citeseer.ist.psu.edu/carbonell98report.html More
@misc{ carbonell98report,
author = "J. Carbonell and M. Craven and S. Fienberg and T. Mitchell and Y. Yang",
title = "Report on the CONALD Workshop on Learning from Text and the Web",
text = "Carbonell, J., Craven, M., Fienberg, S., Mitchell, T., Yang, Y., Report
on the CONALD Workshop on Learning from Text and the Web, 1998.",
year = "1998",
url = "citeseer.ist.psu.edu/carbonell98report.html" }
Citations (may not include all citations):61 Adaptive web sites: an ai challenge - Perkowitz, Etzioni - 1997
21 Text mining with decision rules and decision trees (context) - Apte, Damerau et al.
18 Feature selection for classification based on text hierarchy - Mladenic, Grobelnik
12 Wrapper induction for semistructured Web-based information s.. - Muslea, Minton et al.
11 A probabilistic approach to full-text document clustering - Goldszmidt, Sahami
10 Wrapping semistructured Web pages with finite-state transduc.. (context) - Hsu, Dung
9 Building intelligent agents for Web-based tasks: A theoryref.. - Shavlik, Eliassi-Rad
6 Automated concept extraction from plain text - Gelfand, Wulfekuhler
5 CiteSeer: An autonomous system for processing and organizing.. (context) - Bollacker, Lawrence et al.
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4 Learning correlations between linguistic indicators and sema.. - Radev
4 Active learning with committees: Preliminary results in comp.. (context) - Liere, Tadepalli
4 Learning and representing topic (context) - Hofmann
4 A collaborative filtering agent system for dynamic virtual c.. - de Vel, Nesbitt
3 Information extraction and heuristics for human-like browsin.. (context) - Lacroix, Sahuguet
3 Text mining the Web: Extracting chemical compound names (context) - Fluder
3 Tool for measurement of statistical properties of text (context) - Makagonov, Alexandrov
3 Automated building of a database of neural network papers (context) - Kehagias, Petridis
3 The effect of relevant input information in ID3's learning p.. (context) - Kwon, Kim
3 Automatic learning of a syntactical government patterns dict.. (context) - Gelbukh, Bolshakov et al.
3 Learning for information extraction (context) - Mooney
3 Pool-based active learning for text classifcation (context) - Nigam, McCallum
2 Simultaneous word and document clustering (context) - Lafferty, Venable
1 Event detection (context) - Yang, Pierce et al.
Documents on the same site (http://www.cs.cmu.edu/~yiming/publications.html): More
Topic Detection and Tracking Pilot Study - Allan, Carbonell, Doddington.. (1998) (Correct)
Noise Reduction in a Statistical Approach to Text Categorization - Yang (1995) (Correct)
A Study on Retrospective and On-Line Event Detection - Yang, Pierce, Carbonell (1998) (Correct)
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