A social search evaluation method based on friend clustering in lbsn
An evaluation method and friend technology, applied in the field of social search, can solve the problems of affecting search accuracy, single field, lack of generalization of search object fields, etc., and achieve the effect of accurate and objective search results, dense data, and elimination of singular points
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[0046] Example 1: see figure 1 , figure 2 , a social search evaluation method based on friend clustering in LBSN, described evaluation method comprises the following steps, 1) there are contact information and location information in the Foursquare real data set of crawling, by statistics and analysis to data, extract Contact features, check-in features, evaluation features and time features, a total of 15 data types, including user ID, friend ID, check-in ID, check-in location description, check-in occurrence time zone, check-in location ID, check-in location latitude and longitude, check-in location name, check-in location The type ID of the location, the type name of the check-in location, the time when the check-in occurred, the ID of the evaluation text, the content of the evaluation text, and the time of occurrence of the evaluation, construct a social search model and give a formal description, and filter the data set that occurred in New York. This method is also the ...
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