Abstract: An information retrieval precision evaluation method and device and a computer-readable storage medium. The method includes: retrieving, by virtue of a first predetermined retrieval system, at least one first retrieval result corresponding to a predetermined keyword, and retrieving, by virtue of a second predetermined retrieval system, at least one second retrieval result corresponding to the keyword; generating a first retrieval sequence number corresponding to the first retrieval result and a second retrieval sequence number corresponding to the second retrieval result according to a preset sequence number generation rule; and analyzing the generated first retrieval sequence number and second retrieval sequence number according to a predetermined precision analysis rule to obtain precision of the first retrieval system and the second retrieval system.

Abstract: Disclosed are a method, a terminal, and an apparatus for extracting a headword and a computer-readable storage medium, wherein the method comprises: acquiring a text information input by a user; determining an out-edge weight of each search term of the text information; calculating a linkage-matrix for the each search term; calculating a priori score of the each search term according to a preset document library; determining a random jumping vector for the each search term according to the priori score; calculating a first preliminary score of the each search term according to the linkage-matrix and the random jumping vector; determining a second preliminary score of the each search term according to a preset part-of-speech configuration rule; determining a final degree score of the each search term according to the first preliminary score and the second preliminary score; extracting the headword of the text information according to the final degree score.

Abstract: Disclosed are a method, a terminal, and an apparatus for extracting a headword and a computer-readable storage medium, wherein the method comprises: acquiring a text information input by a user; determining an out-edge weight of each search term of the text information; calculating a linkage-matrix for the each search term; calculating a priori score of the each search term according to a preset document library; determining a random jumping vector for the each search term according to the priori score; calculating a first preliminary score of the each search term according to the linkage-matrix and the random jumping vector; determining a second preliminary score of the each search term according to a preset part-of-speech configuration rule; determining a final degree score of the each search term according to the first preliminary score and the second preliminary score; extracting the headword of the text information according to the final degree score.