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Multilingual Keyword Extraction for Term Suggestion

Multilingual Keyword Extraction for Term Suggestion. Advisor : Dr. Hsu Graduate : Kuo-min Wang Authors : Yuen-Hsien Tseng. 1998 ACM. Outline. Motivation Objective Keyword extraction algorithm Evaluation and Results Conclusions Personal Opinions. Motivation.

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Multilingual Keyword Extraction for Term Suggestion

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  1. Multilingual Keyword Extraction for Term Suggestion Advisor : Dr. Hsu Graduate : Kuo-min Wang Authors :Yuen-Hsien Tseng 1998 ACM .

  2. Outline • Motivation • Objective • Keyword extraction algorithm • Evaluation and Results • Conclusions • Personal Opinions

  3. Motivation • Users of information retrieval systems often input queries containing terms that do not match the terms used to index the majority of the relevant documents. • This problem can use “Term suggestion” to solve.

  4. Objective • Propose Multinlingual keyword Extraction algorithm to solve “Term Suggestion” problem.

  5. Keyword Extraction algorithm • Three steps • 1. Converting the input text into list. • 2. Repeats merging tests until no elements remained to be merged. • 3. Sort the keywords in the final list. • For example • Input text :”BACDBCDABACD” • First step : converts the text into the list(BA:2 AC:2 CD:3 DB:1 BC:1 CD:3 DA:1 AB:1 BA:2 AC:2 CD:3) • Second Step: threshold is 1 • (BAC:2 ACD:2 BAC:2 ACD:2) • (BACD:2 BACD:2) • Finally, List are (BACD:2 BACD:2 CD3)

  6. Evaluation and Results

  7. Conclusions • the proposed multilingual keyword extraction algorithm has some distinct features: • it requires no extra resources such as lexicons, corpora, or NLP parsers. • The time and space complexity are linear in average case. • The threshold, the only parameter in this algorithm, is easily tuned. • Keywords of any length can be identified. • Narrower terms (long keywords) can be extracted as well as broader terms (the corresponding).

  8. Personal Opinions • …

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