Intelligent Systems and Technology (TIST)


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ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Urban Computing, Volume 5 Issue 3, September 2014

Section: Special Section on Urban Computing

Introduction to the Special Section on Urban Computing
Yu Zheng, Licia Capra, Ouri Wolfson, Hai Yang
Article No.: 37
DOI: 10.1145/2642650

Urban Computing: Concepts, Methodologies, and Applications
Yu Zheng, Licia Capra, Ouri Wolfson, Hai Yang
Article No.: 38
DOI: 10.1145/2629592

Urbanization's rapid progress has modernized many people's lives but also engendered big issues, such as traffic congestion, energy consumption, and pollution. Urban computing aims to tackle these issues by using the data that has been generated...

Model-Based Count Series Clustering for Bike Sharing System Usage Mining: A Case Study with the Vélib’ System of Paris
Côme Etienne, Oukhellou Latifa
Article No.: 39
DOI: 10.1145/2560188

Today, more and more bicycle sharing systems (BSSs) are being introduced in big cities. These transportation systems generate sizable transportation data, the mining of which can reveal the underlying urban phenomenon linked to city dynamics. This...

Mining User Check-In Behavior with a Random Walk for Urban Point-of-Interest Recommendations
Josh Jia-Ching Ying, Wen-Ning Kuo, Vincent S. Tseng, Eric Hsueh-Chan Lu
Article No.: 40
DOI: 10.1145/2523068

In recent years, research into the mining of user check-in behavior for point-of-interest (POI) recommendations has attracted a lot of attention. Existing studies on this topic mainly treat such recommendations in a traditional manner—that...

Using Digital Footprints for a City-Scale Traffic Simulation
Gavin Mcardle, Eoghan Furey, Aonghus Lawlor, Alexei Pozdnoukhov
Article No.: 41
DOI: 10.1145/2517028

This article introduces a microsimulation of urban traffic flows within a large-scale scenario implemented for the Greater Dublin region in Ireland. Traditionally, the data available for traffic simulations come from a population census and...

Charging and Storage Infrastructure Design for Electric Vehicles
Marjan Momtazpour, Patrick Butler, Naren Ramakrishnan, M. Shahriar Hossain, Mohammad C. Bozchalui, Ratnesh Sharma
Article No.: 42
DOI: 10.1145/2513567

Ushered by recent developments in various areas of science and technology, modern energy systems are going to be an inevitable part of our societies. Smart grids are one of these modern systems that have attracted many research activities in...

Object-Oriented Travel Package Recommendation
Chang Tan, Qi Liu, Enhong Chen, Hui Xiong, Xiang Wu
Article No.: 43
DOI: 10.1145/2542665

Providing better travel services for tourists is one of the important applications in urban computing. Though many recommender systems have been developed for enhancing the quality of travel service, most of them lack a systematic and open...

Traffic Information Publication with Privacy Preservation
Sashi Gurung, Dan Lin, Wei Jiang, Ali Hurson, Rui Zhang
Article No.: 44
DOI: 10.1145/2542666

We are experiencing the expanding use of location-based services such as AT&T’s TeleNav GPS Navigator and Intel’s Thing Finder. Existing location-based services have collected a large amount of location data, which has great potential...

Measuring and Recommending Time-Sensitive Routes from Location-Based Data
Hsun-Ping Hsieh, Cheng-Te Li, Shou-De Lin
Article No.: 45
DOI: 10.1145/2542668

Location-based services allow users to perform geospatial recording actions, which facilitates the mining of the moving activities of human beings. This article proposes to recommend time-sensitive trip routes consisting of a sequence of locations...

Check-ins in “Blau Space”: Applying Blau’s Macrosociological Theory to Foursquare Check-ins from New York City
Kenneth Joseph, Kathleen M. Carley, Jason I. Hong
Article No.: 46
DOI: 10.1145/2566617

Peter Blau was one of the first to define a latent social space and utilize it to provide concrete hypotheses. Blau defines social structure via social “parameters” (constraints). Actors that are closer together (more homogenous) in...

Section: Special Section on Urban Computing

Home Location Identification of Twitter Users
Jalal Mahmud, Jeffrey Nichols, Clemens Drews
Article No.: 47
DOI: 10.1145/2528548

We present a new algorithm for inferring the home location of Twitter users at different granularities, including city, state, time zone, or geographic region, using the content of users’ tweets and their tweeting behavior. Unlike existing...

Intelligent Interface for Textual Attitude Analysis
Alena Neviarouskaya, Masaki Aono, Helmut Prendinger, Mitsuru Ishizuka
Article No.: 48
DOI: 10.1145/2535912

This article describes a novel intelligent interface for attitude sensing in text driven by a robust computational tool for the analysis of fine-grained attitudes (emotions, judgments, and appreciations) expressed in text. The module responsible...

A Unified Geolocation Framework for Web Videos
Yicheng Song, Yongdong Zhang, Juan Cao, Jinhui Tang, Xingyu Gao, Jintao Li
Article No.: 49
DOI: 10.1145/2533989

In this article, we propose a unified geolocation framework to automatically determine where on the earth a web video was shot. We analyze different social, visual, and textual relationships from a real-world dataset and find four relationships...

Personalized Recommendations of Locally Interesting Venues to Tourists via Cross-Region Community Matching
Yi-Liang Zhao, Liqiang Nie, Xiangyu Wang, Tat-Seng Chua
Article No.: 50
DOI: 10.1145/2532439

You are in a new city. You are not familiar with the places and neighborhoods. You want to know all about the exciting sights, food outlets, and cultural venues that the locals frequent, in particular those that suit your personal interests. Even...

VSRank: A Novel Framework for Ranking-Based Collaborative Filtering
Shuaiqiang Wang, Jiankai Sun, Byron J. Gao, Jun Ma
Article No.: 51
DOI: 10.1145/2542048

Collaborative filtering (CF) is an effective technique addressing the information overload problem. CF approaches generally fall into two categories: rating based and ranking based. The former makes recommendations based on historical rating...