Results 201 to 210 of about 142,696 (248)

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
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +1 more source

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 ...
openaire   +1 more source

An information-theoretic perspective of tf–idf measures

Information Processing & Management, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +2 more sources

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
openaire   +2 more sources

From Tf-Idf to Learning-to-Rank

2016
Ranking 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
openaire   +1 more source

An Improved TF-IDF Approach for Text Classification

Journal of Zhejiang University: Science A, 2005
Yong-Cheng Wang
exaly   +2 more sources