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The evaluation of text string matching algorithms as an aid to image search

Ochelska-Mierzejewska J.

Journal of Applied Computer Science

2018

Vol. 26, nr 1

33--62

The main goal of this paper is to analyse intelligent text string matching methods (like fuzzy sets and relations) and evaluate their usefulness for image search. The present study examines the ability of different algorithms to handle multi-word and multi-sentence queries. Eight different similarity measures (N-gram, Levenshtein distance, Jaro coefficient, Dice coefficient, Overlap coefficient, Euclidean distance, Cosine similarity and Jaccard similarity) are employed to analyse the algorithms in terms of time complexity and accuracy of results. The outcomes are used to develop a hierarchy of methods, illustrating their usefulness to image search. The search response time increases significantly in the case of data sets containing several thousand images. The findings indicate that the analysed algorithms do not fulfil the response-time requirements of professional applications. Due to its limitations, the proposed system should be considered only as an illustration of a novel solution with further development perspectives. The use of Polish as the language of experiments affects the accuracy of measures. This limitation seems to be easy to overcome in the case of languages with simpler grammar rules (e.g. English).

Comparison of string metrics effectiveness for the purpose of estimating the number of unique job offers

Zachara M., Piskor-Ignatowicz C.

Pomiary Automatyka Robotyka

2011

R. 15, nr 12

213-216

The article presents the results of search for a text-comparison method applicable for identifying same or similar job of ers. This is done by calculating pairwise similarity metrics between offers using well known metrics (i.e. Levenshtein, Jaro-Winkler and Jaccard). The article assesses the ef ectiveness of the algorithms and their applicability to the task. Issues related to processing of data of the web pages and computational requirements are also discussed.

W artykule przedstawione zostały rezultaty oceny możliwości zastosowań algorytmów porównywania tekstu dla potrzeb identyfikacji identycznych lub podobnych ogłoszeń o pracę. Do porównań wykorzystano klasyczne metryki (Levenshteina, Jaro-Winklera i Jaccarda). Oceniona została skuteczność i możliwość zastosowania tych algorytmów do przedstawionego zadania. Omówione zostały też kwestie analizy danych pobieranych ze stron www oraz niezbędnych nakładów obliczeniowych.