Lewis, David D. and Hayes. Philip J. (eds.) ACM Transactions on Information Systems, Vol. 12, No. 3, July 1994. Special Issue on Text Categorization. Home/Search Document Not in Database Summary Related Articles Check |
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Theme-Based Retrieval of Web News - Maria (2000) (2 citations) (Correct)
.... in recent years, automatic classification techniques gained much more importance [Salton 1989] There are many exhaustive studies available, comparing several algorithms and techniques, since vast amounts of information became recently accessible (for detailed reviews on some techniques see [Lewis and Hayes 1994; Yang 1997] Automatic information classification is a desirable activity in situations where the dimension of the document corpus becomes dramatically so large that human intervention is impractical. A typical use for automatic text categorization is the classification of news stories ....
LEWIS, D. D. AND HAYES, P. J. 1994. (Eds.) ACM Transactions on Information Systems, Special Issue on Text Categorization. 12(3).
Text Classification and Segmentation Using Minimum Cross-Entropy - Teahan (2000) (2 citations) (Correct)
....mechanism. 4 PPM based text classi cation Text classi cation is the problem of assigning text to any of a set of pre speci ed categories. It is useful in indexing documents for later retrieval, as a stage in natural language processing systems, for content analysis, and in many other roles (Lewis Hayes, 1994). For PPM based classi cation applications, the test text is encoded using PPM models that have been pre trained on text that is (hopefully) representative of the particular style of text being modelled. For example, the style could be a particular language (i.e. English, French or German) it ....
Lewis, D.D. & Hayes, P.J. (1994) \Guest Editorial" in ACM Transactions on Information Systems, 12(3): 231.
A Comparison of Classifiers and Document Representations.. - Schütze, Hull, Pedersen (1995) (11 citations) (Correct)
....Hubble Space Telescope. Our experiments will compare the performance of features based on variable selection to those generated by Latent Semantic Indexing and determine which are more effective for learning algorithms. 3 Learning Algorithms Previous approaches to routing and text categorization [24] have used classification trees [33, 22] Bayesian networks [6] Bayesian classifiers [22, 23] rules induction [1] nearest neighbor techniques [25, 36] logistic regression [5] least square methods [11] discriminant analysis [19] and neural networks [32, 34] The majority of these algorithms ....
David D. Lewis and Philip J. Hayes. Special issue on text categorization. guest editorial. ACM Transactions on Information Systems, 12(3):231, 1994.
Smokey: Automatic Recognition of Hostile Messages - Spertus (1997) (9 citations) (Correct)
....to insults (Dillard and Kinney 1994) have also been measured. Hayakawa and Hayakawa (1990) and Trippett (1986) have written about the emotional content of terms, particularly political ones. Automatic categorization of texts has been a major area of information retrieval research (Lewis 1992, Lewis and Hayes 1994). Sack has written a system to automatically determine the ideological bias of a text (Sack 1995) Email classification through regular expressions is already in use, such as through the mail program extensions Procmail, Mailagent, and Filter. A different method of filtering unstructured text is ....
Lewis, David D. And Hayes, Philip J. Guest Editorial. ACM Transactions on Information Systems 12(3) (July 1994):231.
Information Retrieval and the Statistics of Large Data Sets - Lewis (1996) (1 citation) Self-citation (Lewis) (Correct)
....(e.g. neural nets, decision trees, nearest neighbor classifiers) have been used. Supervised learning is particularly effective in routing (where a user can supply ongoing feedback as the system is used) 7] and in text categorization (where a large body of manually indexed text may be available) [12, 14]. 2 The Future These are exciting times for IR. Statistical IR methods developed over the past 30 years are suddenly being widely applied in everything from shrinkwrapped personal computer software, up to large online databases (Dialog, Lexis Nexis, and West Publishing all fielded their first ....
David D. Lewis and Philip J. Hayes. Guest editorial. ACM Transactions on Information Systems, 12(3):231, July 1994.
Heterogeneous Uncertainty Sampling for Supervised Learning - Lewis, Catlett (1994) (70 citations) Self-citation (Lewis) (Correct)
....step lacks a theoretical justification, performance appeared satisfactory. 4 Task and Data Set The applications motivating this research fall under the heading of text categorization: the classification of instances composed partly or fully of natural language text into pre specified categories [7, 19]. We have found several business applications where categorizing text would aid its use, routing, or analysis. These texts often reside in large databases supporting boolean queries [29, pages 231 236] a restricted version of propositional logic. Because decision rules [27, 34] can be converted ....
David D. Lewis and Philip J. Hayes. Editorial. ACM Transactions on Information Systems. Special Issue on Text Categorization, 1994. To appear.
Information Access - Isaac Cheng And (Correct)
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Lewis, David D. and Hayes. Philip J. (eds.) ACM Transactions on Information Systems, Vol. 12, No. 3, July 1994. Special Issue on Text Categorization.
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