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From Tf-Idf to Learning-to-Rank
2016Ranking a set of documents based on their relevances with respect to a given query is a central problem of information retrieval (IR). Traditionally people have been using unsupervised scoring methods like tf-idf, BM25, Language Model etc., but recently supervised machine learning framework is being used successfully to learn a ranking function, which ...
Muhammad Ibrahim, Manzur Murshed
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Clustering the topics using TF-IDF for model fusion
Proceedings of the 2nd PhD workshop on Information and knowledge management, 2008Users tend to express their queries in various ways: sometimes they use more general terms, sometimes more specific terms. Information retrieval systems need to be able to accommodate this variety of user needs. Some retrieval models perform better when the queries are general, others perform better when the queries are more specific, and others when a
Muath Alzghool, Diana Zaiu Inkpen
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Improvement of TF-IDF Algorithm Based on Knowledge Graph
2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA), 2018The TF-IDF algorithm is commonly used for text information retrieval and data mining. The traditional TF-IDF algorithm does not consider the domain characteristics of the article, and does not consider the distribution ratio. Currently, the solution proposed by many scholars only solves the problems of distribution ratio and the like, and does not ...
Yanpeng Wang +4 more
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Ontology-Based Genes Similarity Calculation with TF-IDF
2012The Gene Ontology (GO) provides a controlled vocabulary of terms for describing genes from different data resources. In this paper, we proposed a novel method determining semantic similarity of genes based on GO. The key principle of our method relies on the introduction of Term Frequency (TF) and Inverse Document Frequency (IDF) to quantify the ...
Yue Huang, Mingxin Gan, Rui Jiang 0001
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A novel TF-IDF weighting scheme for effective ranking
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval, 2013Term weighting schemes are central to the study of information retrieval systems. This article proposes a novel TF-IDF term weighting scheme that employs two different within document term frequency normalizations to capture two different aspects of term saliency.
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An Integrated Approach for the Analysis of the TF/IDF Matrix
2005In this paper we propose to analyse a puculiar data matrix, known as term frequency/inverse document frequency (TF/IDF) matrix, with a strategy based on the jointly use of a Factorial Data Analysis and a Classification Method.
M. MISURACA +2 more
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Using TF-IDF in text classification
AIP Conference Proceedings, 2023Gayrat Juraev, Obidjon Bozorov
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Evaluation of the Delta TF-IDF Features for Sentiment Analysis
2014This paper proposes a feature model different from bag-of-word models to analyze the sentiment of the text. The main idea of the method is improving the quality of prediction by combining a rule-based approach and the standard bag-of-words model. Results of the experiments with changing the subject, the size of reviews in data are shown. The hypothesis
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