C fuzzy string matching
[DOC File]A best-first alignment algorithm for automatic extraction ...
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Fuzzy string matching is also used to identify possible correspondences. We have found that aggressive over-generation of correspondences at this phase is balanced by the more conservative second phase and results in improved overall alignment quality.
[DOCX File]A GENERAL SOLUTION FOR THE PROBLEM OF TNRS: A …
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Prior to submitting names to the parsing and fuzzy-matching applications, family names pre-pended to species names are removed by searching the initial string of the name for standard family endings (“aceae” and “idae”) and checking against a list of conserved plant family names (Gramineae, Compositae, etc.; although plant-specific, the ...
[DOC File]Using Fuzzy k-Modes to Analyze Patterns of System Calls ...
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Step 2) Set c = c+1. Step 3) Find the string with the least entropy value and assign that as centroid to . the c-th fuzzy cluster. Step 4) Remove from all the strings those strings that have a similarity to the. string found in step 3 greater than beta and assign them to the c-th cluster. Step 5) If there are no more strings stop, else go to ...
[DOC File]SAS Data Quality – Cleanse: Techniques for Merge/Purge on ...
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Still, fuzzy matching remains very important. Without well-conceived fuzzy match algorithms, the result is likely to be unsatisfactory, with too many false positives and/or false negatives. SAS-DQ creates match codes for strings based on their characters, locale, and various user-selected settings.
[DOC File]Computational Lexicons and Dictionaries
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More elaborate string matching patterns have proved to be effective when pattern elements specify semantic classes, e.g., “accomplishment” verbs in identifying why a person is famous. Over the six years of the question-answering track, the task has been continually refined to present more difficult questions that would require the use of ...
[DOCX File]MET CS 688 Web Analytics and Mining.docx
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Searching and fuzzy string matching. Clustering text. Classification, categorization, and tagging. Question answering systems. Module 4 - Web Mining. Web Crawlers, Indexing. Searching, precision and recall. Ranking. Module 5 - Applications - Mining the Social Web. Twitter - trending topics, Facebook - Social Graph API.
[DOC File]A WEIGHTED-TREE SIMILARITY ALGORITHM FOR MULTI …
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B. K. Sarker, V. C. Bhavsar, and H. Boley, “A weighted-tree simplicity algorithm for similarity matching of partial product descriptions”, In Proceedings of ISCA 14th International Conference on Intelligent and Adaptive Systems and Software Engineering. Toronto, July 20-22, 2005, pp. 55-60. [14] Yang, L.,
[DOC File]Named Entity Recognition for Indian Languages
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Phonetic matching is a fuzzy string matching technique in which we match strings on the basis of their similar sounding property and not identity. Most common phonetic matching techniques are Soundex and Editex. These techniques are used to match two representations of the same name in English. We survey the techniques in the following subsections.
[DOC File]John Miyamoto - University of Washington
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Searches the R help system for documentation matching a given character string in the (file) name, alias, title, concept or keyword entries (or any combination thereof), using either . fuzzy matching. or . regular expression. matching. Names and titles of the matched help entries are displayed nicely. See also 'RSiteSearch'. identical
John Miyamoto - University of Washington
Searches the R help system for documentation matching a given character string in the (file) name, alias, title, concept or keyword entries (or any combination thereof), using either fuzzy matching. or regular expression. matching. Names and titles of the matched help entries are displayed nicely. See also 'RSiteSearch'.
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