Feature generation for textual information retrieval using world knowledge
ACM SIGIR ForumPublished 1 December 2007
Evgeniy Gabrilovich
Citations38
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
Algorithms present can help an automatic news filtering system that tracks company news understand that the item "Wal-Mart supply chain goes real time" is relevant for the search.
Abstract
Imagine an automatic news filtering system that tracks company news. Given the news item "FDA approves ciprofloxacin for victims of anthrax inhalation", how can the system know that the drug mentioned is an antibiotic produced by Bayer? Or consider an information professional searching for data on RFID technology -- how can a computer understand that the item "Wal-Mart supply chain goes real time" is relevant for the search? Algorithms we present can do just that.
Keywords
Computer Science
The Nature of Statistical Learning Theory
39,279 Citations1995Vladimir Vapnik
C4.5: Programs for Machine Learning
23,665 Citations1992J. R. Quinlan
A complete guide to the C4.5 system as implemented in C for the UNIX environment, which starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting.
Journal of the American Society for Information ScienceIndexing by latent semantic analysis
12,677 Citations1990Scott Deerwester, Susan Dumais +3 more
Language<b>WordNet: An electronic lexical database</b> . Ed. by Christiane Fellbaum. Cambridge, MA: MIT Press, 1998. Pp. xxii, 423.
11,687 Citations2000Adam Kilgarriff
The lexical database: nouns in WordNet, George A. Miller modifiers in WordNet, Katherine J. Miller a semantic network of English verbs, and applications of WordNet: building semantic concordances are presented.
Modern Information Retrieval
11,544 Citations1999Ricardo Baeza‐Yates, Berthier Ribeiro‐Neto
Statistical Comparisons of Classifiers over Multiple Data Sets
11,198 Citations2006Janez Demšar
A set of simple, yet safe and robust non-parametric tests for statistical comparisons of classifiers is recommended: the Wilcoxon signed ranks test for comparison of two classifiers and the Friedman test with the corresponding post-hoc tests for comparisons of more classifiers over multiple data sets.
Foundations of statistical natural language processing
9,996 Citations1999Christopher D. Manning, Hinrich Schütze
Information Processing & ManagementTerm-weighting approaches in automatic text retrieval
9,532 Citations1988Gerard Salton, Chris Buckley
This paper summarizes the insights gained in automatic term weighting, and provides baseline single term indexing models with which other more elaborate content analysis procedures can be compared.
Lecture notes in computer scienceText categorization with Support Vector Machines: Learning with many relevant features
7,925 Citations1998Thorsten Joachims
SVMs achieve substantial improvements over the currently best performing methods and behave robustly over a variety of di-erent learning tasks, eliminating the need for manual parameter tuning.
ACM Computing SurveysMachine learning in automated text categorization
7,899 Citations2002Fabrizio Sebastiani
This survey discusses the main approaches to text categorization that fall within the machine learning paradigm and discusses in detail issues pertaining to three different problems, namely, document representation, classifier construction, and classifier evaluation.
IEEE Transactions on Pattern Analysis and Machine IntelligenceStatistical pattern recognition: a review
6,688 Citations2000Anil K. Jain, Peter Duin +1 more
The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system and identify research topics and applications which are at the forefront of this exciting and challenging field.
Adaptive Signal Processing
5,121 Citations1991
This volume discusses three recently developed general methodologies for designing signal predictors under nonclassical operating conditions, namely the robust predictor, the high-speed Levinson modeling, and the approximate conditional mean nonlinear predictor.
A Comparative Study on Feature Selection in Text Categorization
4,766 Citations1997Yiming Yang, Jan Pedersen
DF thresholding, the simplest method with the lowest cost in computation, can be reliably used instead of IG or CHI when the computation of these measures are too expensive, and strong correlations between the DF, IG and CHI values of a term are found.
Technical reportsMaking Large-Scale SVM Learning Practical
4,317 Citations2006Thorsten Joachims
This chapter presents algorithmic and computational results developed for SVM light V 2.0, which make large-scale SVM training more practical and give guidelines for the application of SVMs to large domains.
The MIT Press eBooksSemi-Supervised Learning
4,308 Citations2006Olivier Chapelle, Schölkopf, B. +1 more
This first comprehensive overview of semi-supervised learning presents state-of-the-art algorithms, a taxonomy of the field, selected applications, benchmark experiments, and perspectives on ongoing and future research.
Meeting of the Association for Computational LinguisticsThumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
3,654 Citations2002Peter Peter, Turney
Machine LearningText Classification from Labeled and Unlabeled Documents using EM
2,749 Citations2000Kamal Nigam, Andrew Kachites McCallum +2 more
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents, and presents two extensions to the algorithm that improve classification accuracy under these conditions.
Transductive Inference for Text Classification using Support Vector Machines
2,717 Citations1999Thorsten Joachims
An analysis of why TSVMs are well suited for text classi(cid:12)cation is presented, and an algorithm for training TSVMs e(cid:14)-ciently, handling 10,000 examples and more is proposed.
A re-examination of text categorization methods
2,660 Citations1999Yiming Yang, Xin Liu
The results show that SVM, kNN and LLSF signi cantly outperform NNet and NB when the number of positive training instances per category are small, and that all the methods perform comparably when the categories are over 300 instances.
Journal of Machine Learning ResearchRCV1: A New Benchmark Collection for Text Categorization Research
2,600 Citations2004David Lewis, Yiming Yang +2 more
This work describes the coding policy and quality control procedures used in producing the RCV1 data, the intended semantics of the hierarchical category taxonomies, and the corrections necessary to remove errorful data.
An extensive empirical study of feature selection metrics for text classification
2,389 Citations2003George Forman
Elsevier eBooksIrrelevant Features and the Subset Selection Problem
2,374 Citations1994George H. John, Ron Kohavi +1 more
A method for feature subset selection using cross-validation that is applicable to any induction algorithm is described, and experiments conducted with ID3 and C4.5 on artificial and real datasets are discussed.
arXiv (Cornell University)Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy
2,224 Citations1997Jay J. Jiang, David W. Conrath
Journal of Artificial Intelligence ResearchSemantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language
2,085 Citations1999Philip Resnik
This article presents a measure of semantic similarity in an IS-A taxonomy based on the notion of shared information content that performs better than the traditional edge-counting approach.
Elsevier eBooksNewsWeeder: Learning to Filter Netnews
2,022 Citations1995Ken Lang
The results show that a learning algorithm based on the Minimum Description Length (MDL) principle was able to raise the percentage of interesting articles to be shown to users from 14% to 52% on average.
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
1,990 Citations2007Evgeniy Gabrilovich, Shaul Markovitch
This work proposes Explicit Semantic Analysis (ESA), a novel method that represents the meaning of texts in a high-dimensional space of concepts derived from Wikipedia that results in substantial improvements in correlation of computed relatedness scores with human judgments.
NatureInternet encyclopaedias go head to head
1,985 Citations2005Jim Giles
Jimmy Wales' Wikipedia comes close to Britannica in terms of the accuracy of its science entries, a Nature investigation finds.
Communications of the ACMCYC
1,947 Citations1995Douglas B. Lenat
The fundamental assumptions of doing such a large-scale project are examined, the technical lessons learned by the developers are reviewed, and the range of applications that are or soon will be enabled by the technology is surveyed.
Information RetrievalAn Evaluation of Statistical Approaches to Text Categorization
1,946 Citations1999Yiming Yang
Analysis and empirical evidence suggest that the evaluation results on some versions of Reuters were significantly affected by the inclusion of a large portion of unlabelled documents, mading those results difficult to interpret and leading to considerable confusions in the literature.
Language and Cognitive ProcessesContextual correlates of semantic similarity
1,584 Citations1991George A. Miller, Walter G. Charles
Transformation-based error-driven learning and natural language processing: a case study in part-of-speech tagging
1,531 Citations1995Eric Brill
This paper describes a simple rule-based approach to automated learning of linguistic knowledge that has been shown for a number of tasks to capture information in a clearer and more direct fashion without a compromise in performance.
Inductive learning algorithms and representations for text categorization
1,465 Citations1998Susan Dumais, John Platt +2 more
A comparison of the effectiveness of five different automatic learning algorithms for text categorization in terms of learning speed, realtime classification speed, and classification accuracy is compared.
Communications of the ACMContextual correlates of synonymy
1,449 Citations1965Herbert Rubenstein, John B. Goodenough
The shapes of the functions indicate that similarity of context is reliable as criterion only for detecting pairs of words that are very similar in meaning.
Computational LinguisticsEvaluating WordNet-based Measures of Lexical Semantic Relatedness
1,414 Citations2006Alexander Budanitsky, Graeme Hirst
An information-content-based measure proposed by Jiang and Conrath is found superior to those proposed by Hirst and St-Onge, Leacock and Chodorow, Lin, and Resnik, and why distributional similarity is not an adequate proxy for lexical semantic relatedness.
Journal of Machine Learning ResearchA Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data
1,372 Citations2005Rie Kubota Ando, Tong Zhang
This paper presents a general framework in which the structural learning problem can be formulated and analyzed theoretically, and relate it to learning with unlabeled data, and algorithms for structural learning will be proposed, and computational issues will be investigated.
ACM SIGIR ForumQuary Expansion Using Local and Global Document Analysis
1,269 Citations2017Jinxi Xu, W. Bruce Croft
It is shown that, although global analysis haa some advantages, local analysia is generally more effective than global techniques and using global analysis techniques.
Corpus-based and knowledge-based measures of text semantic similarity
1,189 Citations2006Rada Mihalcea, Courtney D. Corley +1 more
This paper shows that the semantic similarity method out-performs methods based on simple lexical matching, resulting in up to 13% error rate reduction with respect to the traditional vector-based similarity metric.
Machine LearningExplanation-Based Generalization: A Unifying View
1,175 Citations1986Tom M. Mitchell, Richard M. Keller +1 more
This paper proposes a general, domain-independent mechanism, called EBG, that unifies previous approaches to explanation-based generalization, and is illustrated in the context of several example problems, and used to contrast several existing systems for explanation- based generalization.
A Bayesian Approach to Filtering Junk E-Mail
1,153 Citations1998Mehran Sahami, Susan Dumais +2 more
This work examines methods for the automated construction of filters to eliminate such unwanted messages from a user’s mail stream, and shows the efficacy of such filters in a real world usage scenario, arguing that this technology is mature enough for deployment.
Distributional clustering of English words
994 Citations1993Fernando Pereira, Naftali Tishby +1 more
Placing search in context: the concept revisited.
931 Citations2002Lev Finkelstein, Evgeniy Gabrilovich +5 more
The information bottleneck method
921 Citations2000Naftali Tishby, Fernando C. N. Pereira +1 more
The variational principle provides a surprisingly rich framework for discussing a variety of problems in signal processing and learning, as will be described in detail elsewhere.
Hierarchically Classifying Documents Using Very Few Words
840 Citations1997Daphne Koller, Mehran Sahami
This work proposes an approach that utilizes the hierarchical topic structure to decompose the classification task into a set of simpler problems, one at each node in the classification tree, which can be solved accurately by focusing only on a very small set of features, those relevant to the task at hand.
Machine LearningExplanation-Based Learning: An Alternative View
835 Citations1986Gerald DeJong, Raymond J. Mooney
Six specific problems with the previously proposed framework for the explanation-based approach to machine learning are outlined and an alternative generalization method to perform explanation- based learning of new concepts is presented.
MADOC (University of Mannheim)WikiRelate! computing semantic relatedness using wikipedia
759 Citations2006Michael Strube, Simone Paolo Ponzetto
This work presents experiments on using Wikipedia for computing semantic relatedness and compares it to WordNet on various benchmarking datasets, and shows that Wikipedia outperforms WordNet when applied to the largest available dataset designed for that purpose.
A web-based kernel function for measuring the similarity of short text snippets
743 Citations2006Mehran Sahami, Timothy D. Heilman
This paper defines a similarity kernel function, mathematically analyze some of its properties, and provides examples of its efficacy, and shows the use of this kernel function in a large-scale system for suggesting related queries to search engine users.
Semantic distance in WordNet: An experimental, application-oriented evaluation of five measures
722 Citations2004Alexander Budanitsky, Graeme Hirst +2 more
Distributional clustering of words for text classification
683 Citations1998Lee D. Baker, Andrew Kachites McCallum
This paper describes the application of Distributional Clustering to document classi(cid:12)cation and shows that it can reduce the feature dimensionality by three orders of magnitude and lose only 2% accuracy, better than Latent Semantic In-dexing, class-based clustering, feature selection by mutual information, or Markov-blanket-based feature selection.
Measures of distributional similarity
586 Citations1999Lillian Lee
This work presents an empirical comparison of a broad range of measures; a classification of similarity functions based on the information that they incorporate; and the introduction of a novel function that is superior at evaluating potential proxy distributions.
Improving automatic query expansion
555 Citations1998Mandar Mitra, Amit Singhal +1 more
Experimental results show that refining the set of documents used in query expansion often prevents the query drift caused by blind expansion and yields substantial improvements in retrieval effectiveness, both in terms of average precision and precision in the top twenty documents.
Journal of the ACMAutomatic Indexing: An Experimental Inquiry
552 Citations1961M. E. Maron
The design, execution and evaluation of a modest experimental study aimed at testing empirically one statistical technique for automatic indexed documents according to their subject content are described.
An evaluation of phrasal and clustered representations on a text categorization task
547 Citations1992David Lewis
It is shown that optimal effectiveness occurs when using only a small proportion of the indexing terms available, and that effectiveness peaks at a higher feature set size and lower effectiveness level for a syntactic phrase indexing than for word-based indexing.
ACM Transactions on Information SystemsImproving the effectiveness of information retrieval with local context analysis
533 Citations2000Jinxi Xu, W. Bruce Croft
A new technique is proposed, called local context analysis, which selects expansion terms based on cooccurrence with the query terms within the top-ranked documents.
Training algorithms for linear text classifiers
516 Citations1996David Lewis, Robert E. Schapire +2 more
This work proposes that two machine learning algorithms, the Widrow-Hoff and EG algorithms, be used in training linear text classifiers for IR tasks, and theoretical analysis provides performance guarantees and guidance on parameter settings for these algorithms.
A divisive information theoretic feature clustering algorithm for text classification
513 Citations2003Inderjit S. Dhillon, Subramanyam Mallela +1 more
A new information-theoretic divisive algorithm for feature/word clustering and apply it to text classification is proposed and it is shown that feature clustering is an effective technique for building smaller class models in hierarchical classification.
CERN Document Server (European Organization for Nuclear Research)Roget's Thesaurus of English Words and Phrases
428 Citations1982Betty Kirkpatrick
"Roget's Thesaurus" is the world's most famous and trusted word-finder, essential for anyone who wants to improve their command, creative use and enjoyment of English, and is perfect for composing speeches, or for writing all manner of prose and poetry.
Lecture notes in computer scienceCentroid-Based Document Classification: Analysis and Experimental Results
406 Citations2000Eui-Hong Han, George Karypis
The authors' experiments show that this centroidbased classifier consistently and substantially outperforms other algorithms such as Naive Bayesian, k-nearest-neighbors, and C4.5, on a wide range of datasets.
Overcoming the brittleness bottleneck using wikipedia: enhancing text categorization with encyclopedic knowledge
404 Citations2006Evgeniy Gabrilovich, Shaul Markovitch
It is proposed to enrich document representation through automatic use of a vast compendium of human knowledge--an encyclopedia, and empirical results confirm that this knowledge-intensive representation brings text categorization to a qualitatively new level of performance across a diverse collection of datasets.
The Knowledge Engineering ReviewA survey on the use of relevance feedback for information access systems
403 Citations2003Ian Ruthven, Mounia Lalmas
This paper surveys relevance feedback techniques and studies both automatic techniques, in which the system modifies the user's query, and interactive techniques, which the user has control over query modification.
Machine LearningText Categorization with Support Vector Machines. How to Represent Texts in Input Space?
403 Citations2002Edda Leopold, Jörg Kindermann
It is shown that in the case of text classification, term-frequency transformations have a larger impact on the performance of SVM than the kernel itself.
Machine LearningBoolean Feature Discovery in Empirical Learning
398 Citations1990Giulia Pagallo, David Haussler
Two new methods that adaptively introduce relevant features while learning a decision tree from examples are presented, showing empirically that these methods outperform a standard decision tree algorithm for learning small random DNF functions when the examples are drawn at random from the uniform distribution.
ACM SIGIR ForumExploring the similarity space
386 Citations1998Justin Zobel, Alistair Moffat
It is demonstrated that it is surprisingly difficult to identify which techniques work best, and comment on the experimental methodology required to support any claims as to the superiority of one method over another.
Text classification and named entities for new event detection
364 Citations2004Giridhar Kumaran, James Allan
This paper shows how performance on New Event Detection (NED) can be improved by the use of text classification techniques as well as by using named entities in a new way, and explores modifications to the document representation in a vector space-based NED system.
arXiv (Cornell University)Unsupervised Learning of Semantic Orientation from a Hundred-Billion-Word Corpus
361 Citations2002Peter D. Turney, Michael L. Littman
This paper introduces a simple algorithm for unsupervised learning of semantic orientation from extremely large corpora by issuing queries to a Web search engine and using pointwise mutual information to analyse the results.
Supervised term weighting for automated text categorization
355 Citations2003Franca Debole, Fabrizio Sebastiani
It is proposed that learning from training data should also affect phase (ii), i.e. that information on the membership of training documents to categories be used to determine term weights, and is called supervised term weighting (STW).
A study of thresholding strategies for text categorization
354 Citations2001Yiming Yang
Experimental results show that the choice of thresholding strategy can significantly influence the performance of kNN, and that the ``optimal'' strategy may vary by application.
Machine LearningSimilarity-Based Models of Word Cooccurrence Probabilities
346 Citations1999Ido Dagan, Lillian Lee +1 more
This work proposes a method for estimating the probability of such previously unseen word combinations using available information on “most similar” words, and describes probabilistic word association models based on distributional word similarity, and applies them to two tasks, language modeling and pseudo-word disambiguation.
Annals of Internal MedicineUnlocking Clinical Data from Narrative Reports: A Study of Natural Language Processing
338 Citations1995George Hripcsak, Carol Friedman +4 more
A general-purpose processor is evaluated that is intended to cover various clinical reports and converts narrative reports that are available in electronic form either through word processors or electronic scanning to coded descriptions that are appropriate for automated systems.
Seeing stars when there aren't many stars
319 Citations2006Andrew B. Goldberg, Xiaojin Zhu
A graph-based semi-supervised learning algorithm is presented to address the sentiment analysis task of rating inference and achieves significantly better predictive accuracy over other methods that ignore the unlabeled examples during training.
Journal of Intelligent Information SystemsA Study of Approaches to Hypertext Categorization
309 Citations2002Yiming Yang, Seán Slattery +1 more
This paper examines five hypertext regularities which may (or may not) hold in a particular application domain, and whose presence (or absence) may significantly influence the optimal design of a classifier.
High-performing feature selection for text classification
304 Citations2002Monica Rogati, Yiming Yang
It is found that feature selection methods based on chi2 statistics consistently outperformed those based on other criteria (including information gain) for all four classifiers and both data collections, and that a further increase in performance was obtained by combining uncorrelated and high-performing feature selection Methods.
Phrasal translation and query expansion techniques for cross-language information retrieval
303 Citations1997Lisa Ballesteros, W. Bruce Croft
The role of phrases in query expansion via local context analysis and local feedback and how they can be used to significantly reduce the error associated with automatic dictionary translation are explored.
Constructing informative priors using transfer learning
299 Citations2006Rajat Raina, Andrew Y. Ng +1 more
An algorithm for automatically constructing a multivariate Gaussian prior with a full covariance matrix for a given supervised learning task, which relaxes a commonly used but overly simplistic independence assumption, and allows parameters to be dependent.
Distributional word clusters vs. words for text categorization
282 Citations2003Ron Bekkerman, Ran El‐Yaniv +2 more
Generalized vector spaces model in information retrieval
267 Citations1985S. K. M. Wong, Wojciech Ziarko +1 more
This paper proposes a systematic method (the generalized vector space model) to compute term correlations directly from automatic indexing scheme and demonstrates how such correlations can be included with minimal modification in the existing vector based information retrieval systems.
Improving pseudo-relevance feedback in web information retrieval using web page segmentation
249 Citations2003Shipeng Yu, Deng Cai +2 more
This paper proposes a VIsion-based Page Segmentation (VIPS) algorithm to detect the semantic content structure in a web page and achieves 27% performance improvement on Web Track dataset.
The reuters corpus volume 1 - From yesterday's news to tomorrow's language resources
249 Citations2002Tony Rose, Mark Stevenson +1 more
The origins of RCV1, the motivations behind its creation, and how it differs from previous corpora are described, and the system of category coding, whereby each story is annotated for topic, region and industry sector is discussed.
Information RetrievalHierarchical Text Categorization Using Neural Networks
248 Citations2002Miguel E. Ruiz, Padmini Srinivasan
The results show that the use of the hierarchical structure improves text categorization performance with respect to an equivalent flat model, and the optimized Rocchio algorithm achieves a performance comparable with that of the Hierarchical Mixture of Experts model.
Information RetrievalAugmenting Naive Bayes Classifiers with Statistical Language Models
247 Citations2004Fuchun Peng, Dale Schuurmans +1 more
This paper introduces CAN models, a generalized naive Bayes classifier which allows for a local Markov dependence among observations, and systematically study the key factors in the CAN model that can influence the classification performance, and analyze the strengths and weaknesses.
E-LIS Repository (University of Naples Federico II)Open Directory Project
235 Citations2003Víctor Pàmies
Evaluating text categorization
234 Citations1991David Lewis
Feature generation for text categorization using world knowledge
232 Citations2005Evgeniy Gabrilovich, Shaul Markovitch
Improved machine learning algorithms for text categorization with generated features based on domain-specific and common-sense knowledge are enhanced, addressing the two main problems of natural language processing--synonymy and polysemy.
A high-performance semi-supervised learning method for text chunking
223 Citations2005Rie Kubota Ando, Tong Zhang
A novel semi-supervised method that employs a learning paradigm which is to find "what good classifiers are like" by learning from thousands of automatically generated auxiliary classification problems on unlabeled data, which produces performance higher than the previous best results.
Newsjunkie
220 Citations2004Evgeniy Gabrilovich, Susan Dumais +1 more
Newsjunkie is described, a system that personalizes news for users by identifying the novelty of stories in the context of stories they have already reviewed, and employs novelty-analysis algorithms that represent articles as words and named entities.
Lecture notes in computer scienceExperiments on the Use of Feature Selection and Negative Evidence in Automated Text Categorization
209 Citations2000Luigi Galavotti, Fabrizio Sebastiani +1 more
This work proposes a novel variant, based on the exploitation of negative evidence, of the well-known k-NN method, and reports the results of systematic experimentation of these two methods performed on the standard REUTERS-21578 benchmark.
Text categorization with many redundant features
202 Citations2004Evgeniy Gabrilovich, Shaul Markovitch
A novel measure is developed that captures feature redundancy, and is used to analyze a large collection of datasets and shows that for problems plagued with numerous redundant features the performance of C4.5 is significantly superior to that of SVM, while aggressive feature selection allows SVM to beat C 4.5 by a narrow margin.
Neural Information Processing SystemsTransfer learning for text classification
187 Citations2005Joshua Shulman, Andrew Y. Ng
This paper proposes an algorithm for automatically learning a parameter function from related classification problems, and defines a new learning algorithm for text classification, which it finds outperforms existing methods on a variety of multiclass text classification tasks.
Constructive induction on decision trees
187 Citations1989Christopher J. Matheus, Larry Rendell
A definition of feature construction in concept learning is presented, and a framework for its study is offered based on four aspects: detection, selection, generalization, and evaluation.
Adelaide Research & Scholarship (AR&S) (University of Adelaide)An Empirical Evaluation of Models of Text Document Similarity
185 Citations2005Michael Lee, Brandon Pincombe +1 more
An attempt to establish a ‘psychological ground truth’ for evaluating models of the ability of word-based, n-gram and Latent Semantic Analysis approaches to model human judgments of text document similarity is reported.
A learner-independent evaluation of the usefulness of statistical phrases for automated text categorization
180 Citations2001Maria Fernanda Caropreso, Stan Matwin +1 more
This work investigates the usefulness of n-grams for document indexing in text categorization (TC) independently of any specific learning algorithm, by applying feature selection to the pool of all k- grams, and checking how many n- Grams score high enough to be selected in the top σ k-rams.
Discovering missing links in Wikipedia
179 Citations2005Sisay Fissaha Adafre, Maarten de Rijke
The method is proposed consists of two steps: first, a cluster of highly similar pages around a given page is computed, and then candidate links from those similar pages that might be missing on the given page are identified.
A Probabilistic Model of Redundancy in Information Extraction
177 Citations2006Doug Downey, Oren Etzioni +1 more
A combinatorial "balls-andurns" model is introduced that computes the impact of sample size, redundancy, and corroboration from multiple distinct extraction rules on the probability that an extraction is correct.
Yahoo! as an ontology
176 Citations1999Yannis Labrou, Tim Finin
The findings suggest that the best results occur when using the very brief descriptions of the Yahoo! categorized entries; these brief descriptions are provided either by the entries' submitters or by the Yahoo!. human indexers and accompany most Yahoo!-indexed entries.
Lecture notes in computer scienceFeature subset selection in text-learning
171 Citations1998Dunja Mladenić
Experimental comparison given on real-world data collected from Web users shows that characteristics of the problem domain and machine learning algorithm should be considered when feature scoring measure is selected.
Lecture notes in computer scienceCombining Naive Bayes and n-Gram Language Models for Text Classification
170 Citations2003Fuchun Peng, Dale Schuurmans
This work augments the naive Bayes model with an n-gram language model to address two shortcomings of naive Baye text classifiers and shows that smoothing techniques from statistical language modeling can be used to recover better estimates than the Laplace smoothing technique usually used in naive Bayed classification.
arXiv (Cornell University)Measuring Semantic Similarity by Latent Relational Analysis
165 Citations2005Peter D. Turney
Machine LearningFeature Generation Using General Constructor Functions
142 Citations2002Shaul Markovitch, Dan Rosenstein
A generalized and flexible framework that is capable of generating features from any given set of constructor functions, and was applied to a variety of classification problems and was able to generate features that were strongly related to the underlying target concepts.
The MIT Press eBooksUsing WordNet for Text Retrieval
140 Citations1998
This chapter contains sections titled: Introduction, Text Retrreval Background, Concept Matching, Query Expansion, Conclusion, References.
Using Taxonomy, Discriminants, and Signatures for Navigating in Text Databases
130 Citations1997Soumen Chakrabarti, Byron Dom +2 more
This work uses techniques from statistical pattern recognition to efficiently separate the feature words or discriminants from the noise words at each node of the taxonomy, and builds a multi-level classifier that has a small model size and is very fast.
On feature distributional clustering for text categorization
124 Citations2001Ron Bekkerman, Ran El‐Yaniv +2 more
This work describes a text categorization approach that is based on a combination of feature distributional clusters with a support vector machine (SVM) classifier that yields high performance text classification that can outperform other recent methods in terms of categorization accuracy and representation efficiency.
…