Double-hash table association method for inquiring interval durability top-k

Abstract

The invention discloses a double-hash table association method for inquiring interval durability top-k, comprising the following steps: inputting a keyword and an inquiry time range; establishing an inverted table, dividing inquiry time into a plurality of spacing intervals, and establishing a first hash table and a second hash table according to the inverted table and the spacing interval; if total score inquired and recorded at the last in each inverted table of the second has table is less than currently-inquired and recorded total score of the same inquired document ID corresponding to a document version having a corresponding ID with effective spacing interval of the first hash table in different inverted tables, ordering the total score inquired and recorded at the last in each inverted table of the second has table in a descending order, and outputting the document ID corresponding to the previous K total scores and spacing intervals thereof; adding the spacing intervals with the same document ID, ordering an adding result in the descending order and outputting the document ID corresponding to the previous results. According to the invention, a method for inquiring a time length of score of the document version within the time range in a top-k result set is realized, wherein the time length meets a threshold.

Description

technical field [0001] The invention relates to the field of database and query, in particular to a double hash table association method for interval persistent top-k query. Background technique [0002] With the rapid development of the Internet and the explosive growth of information volume, it is becoming more and more difficult to accurately search for the information users need. How to find the information that users are most concerned about from massive data has become a common concern in the industry. Therefore, the top-k query technique emerges, which returns the k most important results in the latent data space according to the scoring function. This technology is very effective and has been very mature, widely used in various fields. It effectively solves the ranking problem of precise query from massive data, and together with the full-text search technology, has made a great contribution to the field of database query, and is very popular among users. Documents...

AI Technical Summary

Problems solved by technology

DDA is an improvement to the search method and the greedy method. The threshold is set to query results as soon as possible, but it needs to record the upper and lower boundaries for each tuple, which will occupy a large amount of storage space. The BBA algorithm is an optimization of the previous algorithms. , it also requires a lot of storage space to save the record segments of candidate bands and top-k bands

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