Geolocation as a digital phenotyping measure of negative symptoms and functional outcome

IM Raugh, SH James, CM Gonzalez… - Schizophrenia …, 2020 - academic.oup.com
Objective Negative symptoms and functional outcome have traditionally been assessed
using clinical rating scales, which rely on retrospective self-reports and have several …

Location recommendation by combining geographical, categorical, and social preferences with location popularity

Y Ma, J Mao, Z Ba, G Li - Information Processing & Management, 2020 - Elsevier
The primary aim of location recommendation is to predict users' future movement by
modeling user preference. Multiple types of information have been adopted in profiling …

Geosocial co-clustering: A novel framework for geosocial community detection

J Kim, JG Lee, BS Lee, J Liu - ACM Transactions on Intelligent Systems …, 2020 - dl.acm.org
As location-based services using mobile devices have become globally popular these days,
social network analysis (especially, community detection) increasingly benefits from …

A survey on analysis of user behavior on digital market by mining clickstream data

PK Padigela, R Suguna - … of the Third International Conference on …, 2020 - Springer
Data stream mining has emerged as one of the most prominent areas with its applications in
various areas like network sensors, stock exchange, meteorological research and e …

GSSM: An Integration Model of Heterogeneous Factors for Point-of-Interest Recommendation

Q Yang, Y Chen, P Luo, J Zhang - … , ICAIS 2020, Hohhot, China, July 17–20 …, 2020 - Springer
Millions of users prefer to share their locations and social relationships on location-based
social networks (LBSNs), such as Gowalla, Foursquare, and etc. It has become an important …

[PDF][PDF] Community based Personalized Location Recommendation System

KMSMA Mahmood, NR Darwesh - researchgate.net
this paper introduces Community Based Personalized Location Recommendation System
(CMP) framework that provides the user based on their personal preferences with the most …