Intelligent Systems and Technology (TIST)


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ACM Transactions on Intelligent Systems and Technology (TIST) - Survey Paper, Regular Papers and Special Section on Participatory Sensing and Crowd Intelligence, Volume 6 Issue 3, May 2015

Section: Survey Paper

Trajectory Data Mining: An Overview
Yu Zheng
Article No.: 29
DOI: 10.1145/2743025

The advances in location-acquisition and mobile computing techniques have generated massive spatial trajectory data, which represent the mobility of a diversity of moving objects, such as people, vehicles, and animals. Many techniques have been...

Section: Survey Paper

Identifying Authorities in Online Communities
Mohamed Bouguessa, Lotfi Ben Romdhane
Article No.: 30
DOI: 10.1145/2700481

Several approaches have been proposed for the problem of identifying authoritative actors in online communities. However, the majority of existing methods suffer from one or more of the following limitations: (1) There is a lack of an automatic...

Who Will Retweet This? Detecting Strangers from Twitter to Retweet Information
Kyumin Lee, Jalal Mahmud, Jilin Chen, Michelle Zhou, Jeffrey Nichols
Article No.: 31
DOI: 10.1145/2700466

There has been much effort on studying how social media sites, such as Twitter, help propagate information in different situations, including spreading alerts and SOS messages in an emergency. However, existing work has not addressed how to...

Simplifying Data Disclosure Configurations in a Cloud Computing Environment
Ron Hirschprung, Eran Toch, Oded Maimon
Article No.: 32
DOI: 10.1145/2700472

Cloud computing offers a compelling vision of computation, enabling an unprecedented level of data distribution and sharing. Beyond improving the computing infrastructure, cloud computing enables a higher level of interoperability between...

User-Specific Feature-Based Similarity Models for Top-n Recommendation of New Items
Asmaa Elbadrawy, George Karypis
Article No.: 33
DOI: 10.1145/2700495

Recommending new items for suitable users is an important yet challenging problem due to the lack of preference history for the new items. Noncollaborative user modeling techniques that rely on the item features can be used to recommend new items....

TerraFly GeoCloud: An Online Spatial Data Analysis and Visualization System
Mingjin Zhang, Huibo Wang, Yun Lu, Tao Li, Yudong Guang, Chang Liu, Erik Edrosa, Hongtai Li, Naphtali Rishe
Article No.: 34
DOI: 10.1145/2700494

With the exponential growth of the usage of web map services, geo-data analysis has become more and more popular. This article develops an online spatial data analysis and visualization system, TerraFly GeoCloud, which helps end-users visualize...

Significant Correlation Pattern Mining in Smart Homes
Yi-Cheng Chen, Wen-Chih Peng, Jiun-Long Huang, Wang-Chien Lee
Article No.: 35
DOI: 10.1145/2700484

Owing to the great advent of sensor technology, the usage data of appliances in a house can be logged and collected easily today. However, it is a challenge for the residents to visualize how these appliances are used. Thus, mining algorithms are...

Section: Survey Paper

An Introduction to the Special Issue on Participatory Sensing and Crowd Intelligence
Bin Guo, Alvin Chin, Zhiwen Yu, Runhe Huang, Daqing Zhang
Article No.: 36
DOI: 10.1145/2745712

Sensing the Pulse of Urban Refueling Behavior: A Perspective from Taxi Mobility
Fuzheng Zhang, Nicholas Jing Yuan, David Wilkie, Yu Zheng, Xing Xie
Article No.: 37
DOI: 10.1145/2644828

Urban transportation is an important factor in energy consumption and pollution, and is of increasing concern due to its complexity and economic significance. Its importance will only increase as urbanization continues around the world. In this...

Ohmage: A General and Extensible End-to-End Participatory Sensing Platform
H. Tangmunarunkit, C. K. Hsieh, B. Longstaff, S. Nolen, J. Jenkins, C. Ketcham, J. Selsky, F. Alquaddoomi, D. George, J. Kang, Z. Khalapyan, J. Ooms, N. Ramanathan, D. Estrin
Article No.: 38
DOI: 10.1145/2717318

Participatory sensing (PS) is a distributed data collection and analysis approach where individuals, acting alone or in groups, use their personal mobile devices to systematically explore interesting aspects of their lives and communities [Burke...

EEMC: Enabling Energy-Efficient Mobile Crowdsensing with Anonymous Participants
Haoyi Xiong, Daqing Zhang, Leye Wang, J. Paul Gibson, Jie Zhu
Article No.: 39
DOI: 10.1145/2644827

Mobile Crowdsensing (MCS) requires users to be motivated to participate. However, concerns regarding energy consumption and privacy—among other things—may compromise their willingness to join such a crowd. Our preliminary observations...

City-Scale Social Event Detection and Evaluation with Taxi Traces
Wangsheng Zhang, Guande Qi, Gang Pan, Hua Lu, Shijian Li, Zhaohui Wu
Article No.: 40
DOI: 10.1145/2700478

A social event is an occurrence that involves lots of people and is accompanied by an obvious rise in human flow. Analysis of social events has real-world importance because events bring about impacts on many aspects of city life. Traditionally,...

Activity Sensor: Check-In Usage Mining for Local Recommendation
Jitao Sang, Tao Mei, Changsheng Xu
Article No.: 41
DOI: 10.1145/2700468

While on the go, people are using their phones as a personal concierge discovering what is around and deciding what to do. Mobile phone has become a recommendation terminal customized for individuals—capable of recommending activities and...

An Event-Driven QoI-Aware Participatory Sensing Framework with Energy and Budget Constraints
Bo Zhang, Zheng Song, Chi Harold Liu, Jian Ma, Wendong Wang
Article No.: 42
DOI: 10.1145/2630074

Participatory sensing systems can be used for concurrent event monitoring applications, like noise levels, fire, and pollutant concentrations. However, they are facing new challenges as to how to accurately detect the exact boundaries of these...