公开(公告)号：US20150127482A1

公开(公告)日：2015-05-07

申请号：US14096149

申请日：2013-12-04

Applicant: Institute for Information Industry

Inventor： Grace Lin ,  Meng-Jung Shih ,  Ya-Hui Chan ,  Ting-Yu Lin ,  Yi-Hsin Wu ,  Hsi-Chuan Chen

IPC: G06Q30/06

CPC classification number: G06Q30/0631

Abstract: A merchandise recommendation method for multiple users used in a merchandise recommendation system including a user database, a merchandise database, a data transmission module, a processing module and a memory is provided. The merchandise recommendation method includes the steps outlined below. The processing module receives participant information and target merchandise information from a remote originator host. The processing module retrieves corresponding user information from the user database according to the participant information. The processing module retrieves corresponding merchandise information from the merchandise database according to the target merchandise information. The processing module analyzes social influence information and preference information included in the user information and analyzes the merchandise information to generate an analysis result. The processing module generates composite merchandise recommendation information according to the analysis result.

Abstract translation: 提供了一种在包括用户数据库，商品数据库，数据传输模块，处理模块和存储器的商品推荐系统中使用的多个用户的商品推荐方法。 商品推荐方法包括以下步骤。 处理模块从远程发起者主机接收参与者信息和目标商品信息。 处理模块根据参与者信息从用户数据库检索相应的用户信息。 处理模块根据目标商品信息从商品数据库检索相应的商品信息。 处理模块分析用户信息中包含的社会影响信息和偏好信息，并分析商品信息以生成分析结果。 处理模块根据分析结果生成复合商品推荐信息。

公开(公告)号：US20170148043A1

公开(公告)日：2017-05-25

申请号：US14965631

申请日：2015-12-10

Applicant: INSTITUTE FOR INFORMATION INDUSTRY

Inventor： Yi-Chun Chen ,  De-Nian Yang ,  Pei-Yu Hsieh ,  Grace Lin ,  Ya-Hui Chan

IPC: G06Q30/02

CPC classification number: G06Q30/0205 ,  G06Q30/0206 ,  G06Q30/0246 ,  G06Q30/0251 ,  G06Q30/0261

Abstract: A location based community integration matchmaking system, method and computer readable recording media for optimizing sales is provided, including: obtaining user behavior pattern in an inquired area range based on stores information and user behavioral sequential information; calculating a location based community influence degree of each user in the inquired area range toward other location based users in a community based on the user behavior pattern, the community association and behavioral information, and calculating an interest domain influence degree of each user toward each interest domain; obtaining influence diffusing degree of each user toward each interest domain based on the location based community influence and the interest domain influence degree of each user; and finding a range with large influence degree in the inquired area range for performing advertisement setting, thereby achieving optimization analysis and visitor maximization of marketing channel of brick and mortar stores in the area.