Results 211 to 220 of about 136,207 (260)

TF-IDF uncovered

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, 2008
Interpretations of TF-IDF are based on binary independence retrieval, Poisson, information theory, and language modelling. This paper contributes a review of existing interpretations, and then, TF-IDF is systematically related to the probabilities P(q|d) and P(d|q). Two approaches are explored: a space of independent, and a space of disjoint terms. For
Thomas Roelleke, Jun Wang 0032
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Sentiment Enhanced Hybrid TF-IDF for Microblogs

2014 IEEE Fourth International Conference on Big Data and Cloud Computing, 2014
As the usage of social networks grows day by day, a single person can reach hundreds or thousands of people in a minute. Micro blogging is the new era of social communication, which can be used anywhere thanks to mobile phones. People spend hours and use social networks extensively, expressing their feelings, interests and dislikes. If this data can be
Atakan Simsek, Pinar Karagoz
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Using TF-IDF to hide sensitive itemsets

Applied Intelligence, 2012
Data mining technology helps extract usable knowledge from large data sets. The process of data collection and data dissemination may, however, result in an inherent risk of privacy threats. Some sensitive or private information about individuals, businesses and organizations needs to be suppressed before it is shared or published.
Tzung-Pei Hong, Chun-Wei Lin 0001, Kuo-Tung Yang, Shyue-Liang Wang   +3 more
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Improvement and Application of TF * IDF Algorithm

2011
The traditional TF-IDF probability model is a relatively simple formula. For a few words which are commonly used and not stop words in a paper,it is lack of better differentiate and is not suitable for many specific cases, such as news advertising service module, about extraction of key words of the article, according to the deficiencies and the demand
Ji-Rui Li, Yan-Fang Mao, Kai Yang
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Document clustering: TF-IDF approach

2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), 2016
Recent advances in computer and technology resulted into ever increasing set of documents. The need is to classify the set of documents according to the type. Laying related documents together is expedient for decision making. Researchers who perform interdisciplinary research acquire repositories on different topics.
Prafulla Bafna, Dhanya Pramod, Anagha Vaidya   +2 more
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Research on case reasoning method based on TF-IDF

International Journal of System Assurance Engineering and Management, 2021
With the continuous expansion of the application field of Case-Based Reasoning (CBR) technology, it is increasingly difficult for programmers to acquire and express professional knowledge. Therefore, this paper first gives a structured expression of professional knowledge, and combines the Case-Based Reasoning method with the scientific measurement of ...
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An information-theoretic perspective of tf–idf measures

Information Processing & Management, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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The Automatic option of inference rules for the fuzzy TF-IDF

2020 IEEE 2nd International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS), 2020
For several NLP tasks, we use the Fuzzy Inference System (FIS) to develop a set of decisional systems. Still, the selection rules FIS process needs some modification to be more useful. In this paper, we use FIS to produce terms weight for electronic documents basing on the popular TF-IDF (term frequency-inverse term frequency) components.
Mariem Bounabi, Karim El Moutaouakil, Khalid Satori   +2 more
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Movie genre classification using TF-IDF and SVM

Proceedings of the 2019 7th International Conference on Information Technology: IoT and Smart City, 2019
This paper studies the classification principle and process of SVM algorithm, and classifies the text containing movie information, so as to achieve the research purpose of movie classification. It focuses on the various steps that need to be completed in the process of classification, such as text word segmentation, feature engineering, text ...
Ning Fei, Yangyang Zhang
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Chinese readability assessment using TF-IDF and SVM

2011 International Conference on Machine Learning and Cybernetics, 2011
This paper proposes a simple yet effective method to automatically determine the readability of Chinese articles. We use mutual information to select the most important terms from the training data, calculate TF-IDF values based on those terms, and use those values as features for SVM to build classification models that identify articles suitable for ...
Yaw-Huei Chen, Yi-Han Tsai, Yu-Ta Chen
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