Temat: vector space model - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: A study of parallel techniques for dimensionality reduction and its impact on the quality of text processing algorithms
Autorzy:: Pietroń, M.
Wielgosz, M.
Karwatowski, M.
Wiatr, K.
Powiązania:: https://bibliotekanauki.pl/articles/114190.pdf
Data publikacji:: 2015
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:: singular value decomposition
vector space model
TFIDF
Opis:: The presented algorithms employ the Vector Space Model (VSM) and its enhancements such as TFIDF (Term Frequency Inverse Document Frequency) with Singular Value Decomposition (SVD). TFIDF were applied to emphasize the important features of documents and SVD was used to reduce the analysis space. Consequently, a series of experiments were conducted. They revealed important properties of the algorithms and their accuracy. The accuracy of the algorithms was estimated in terms of their ability to match the human classification of the subject. For unsupervised algorithms the entropy was used as a quality evaluation measure. The combination of VSM, TFIDF, and SVD came out to be the best performing unsupervised algorithm with entropy of 0.16.
Źródło:: Measurement Automation Monitoring; 2015, 61, 7; 352-353
2450-2855
Pojawia się w:: Measurement Automation Monitoring
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Document Clustering : Concepts, Metrics and Algorithms
Autorzy:: Tarczynski, T.
Powiązania:: https://bibliotekanauki.pl/articles/226231.pdf
Data publikacji:: 2011
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: document clustering
text mining
k-means
hierarchical clustersting
vector space model
Opis:: Document clustering, which is also refered to as text clustering, is a technique of unsupervised document organisation. Text clustering is used to group documents into subsets that consist of texts that are similar to each orher. These subsets are called clusters. Document clustering algorithms are widely used in web searching engines to produce results relevant to a query. An example of practical use of those techniques are Yahoo! hierarchies of documents [1]. Another application of document clustering is browsing which is defined as searching session without well specific goal. The browsing techniques heavily relies on document clustering. In this article we examine the most important concepts related to document clustering. Besides the algorithms we present comprehensive discussion about representation of documents, calculation of similarity between documents and evaluation of clusters quality.
Źródło:: International Journal of Electronics and Telecommunications; 2011, 57, 3; 271-277
2300-1933
Pojawia się w:: International Journal of Electronics and Telecommunications
Dostawca treści:: Biblioteka Nauki

Artykuł

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