METHOD AND SERVER FOR SELECTING RECOMMENDATION ITEMS FOR A USER

METHOD AND SERVER FOR SELECTING RECOMMENDATION ITEMS FOR A USER

A method and server for selecting recommendation items is provided. The method comprises receiving indication of user accessing a recommendation service. The method comprises determining a user-type of user being one of a new-user and old-user type. The method comprises, responsive to the user being...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: DANILCHENKO, Andrey Petrovich, ZHIVOTVOREV, Dmitry Sergeevich
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:A method and server for selecting recommendation items is provided. The method comprises receiving indication of user accessing a recommendation service. The method comprises determining a user-type of user being one of a new-user and old-user type. The method comprises, responsive to the user being of the new-user type: receiving information associated with a set of items from a landing page of a pre-determined resource being indicative of visual characteristics of the items; generating a feature vector for each item based on information associated with visual characteristics; generating by an MLA a user-non-specific popularity score for each item from based on the respective feature vector; generating a set of user-non-specific recommendation items by selecting from the items user-non-specific recommendation items to be presented to the user; and transmitting the set of user-non-specific recommendation items in lieu of the personalized content recommendation. A method of training the MLA is also provided.