Ntt Docomo, Inc.

Anna Oonishi

Yusuke Fukazawa

Satoshi Kawasaki

A POI popularity derivation device () includes: a dictionary generation unit () that assigns a feature word used as a co-occurrence word of a POI name to each popularity-assigned POI name serving as a popularity assignment target to generate a popularity-assigned POI dictionary in which a popularity-assigned POI name and a feature word are associated with each other; an extraction unit () that extracts posted data serving as a search target from posted data on the basis of predetermined criteria; and a popularity derivation unit () that searches for the posted data on the basis of a predetermined rule regarding feature words while referring to the popularity-assigned POI dictionary, to extract posted data linked to the popularity-assigned POI name, and derives the popularity of each popularity-assigned POI name on the basis of the number of pieces of extracted posted data for each popularity-assigned POI name.

POI popularity derivation device

A popularity estimation device includes: an acquisition unit configured to acquire a first map image including a first particular point and to acquire a plurality of second map images including a second particular point which is a particular point; a generation unit configured to generate a first feature vector and a second feature vector by inputting the first map image and the second map images to a geographical feature generation model with a map image as an input and with a feature vector indicating geographical features of the map image as an output; a score calculating unit configured to calculate a popularity score of the first particular point from a popularity score of the second particular point based on a degree of similarity between the first feature vector and the second feature vector; and an output unit configured to output the popularity score of the first particular point.

Popularity evaluation system and geographical feature generation model

Provided is a re-ranking device that enables a re-ranking process with less possibility of decrease in accuracy due to shortage of data. A re-ranking deviceincludes an input unitthat receives a search query from one user, a re-ranking model storage unitthat stores a plurality of re-ranking models prepared in accordance with common information of a plurality of users, a search unitthat performs a search on the basis of the search query and obtains a search result, and a re-ranking processing unitthat selects one re-ranking model on the basis of common information of the one user and performs a re-ranking process on the search result using the one re-ranking model.

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Chiyoda-ku, Japan

Anna Oonishi