Intelligent Systems and Technology (TIST)


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ACM Transactions on Intelligent Systems and Technology (TIST), Volume 8 Issue 1, October 2016

SNAP: A General-Purpose Network Analysis and Graph-Mining Library
Jure Leskovec, Rok Sosič
Article No.: 1
DOI: 10.1145/2898361

Large networks are becoming a widely used abstraction for studying complex systems in a broad set of disciplines, ranging from social-network analysis to molecular biology and neuroscience. Despite an increasing need to analyze and manipulate...

Topic-Aware Physical Activity Propagation with Temporal Dynamics in a Health Social Network
Nhathai Phan, Javid Ebrahimi, David Kil, Brigitte Piniewski, Dejing Dou
Article No.: 2
DOI: 10.1145/2873066

Modeling physical activity propagation, such as activity level and intensity, is a key to preventing obesity from cascading through communities, and to helping spread wellness and healthy behavior in a social network. However, there have not been...

Multiagent Resource Allocation for Dynamic Task Arrivals with Preemption
John A. Doucette, Graham Pinhey, Robin Cohen
Article No.: 3
DOI: 10.1145/2875441

In this article, we present a distributed algorithm for allocating resources to tasks in multiagent systems, one that adapts well to dynamic task arrivals where new work arises at short notice. Our algorithm is designed to leverage preemption if...

Dynamic Scheduling of Cybersecurity Analysts for Minimizing Risk Using Reinforcement Learning
Rajesh Ganesan, Sushil Jajodia, Ankit Shah, Hasan Cam
Article No.: 4
DOI: 10.1145/2882969

An important component of the cyber-defense mechanism is the adequate staffing levels of its cybersecurity analyst workforce and their optimal assignment to sensors for investigating the dynamic alert traffic. The ever-increasing cybersecurity...

Using Scalable Data Mining for Predicting Flight Delays
Loris Belcastro, Fabrizio Marozzo, Domenico Talia, Paolo Trunfio
Article No.: 5
DOI: 10.1145/2888402

Flight delays are frequent all over the world (about 20% of airline flights arrive more than 15min late) and they are estimated to have an annual cost of billions of dollars. This scenario makes the prediction of flight delays a primary...

Recognizing Parkinsonian Gait Pattern by Exploiting Fine-Grained Movement Function Features
Tianben Wang, Zhu Wang, Daqing Zhang, Tao Gu, Hongbo Ni, Jiangbo Jia, Xingshe Zhou, Jing Lv
Article No.: 6
DOI: 10.1145/2890511

Parkinson's disease (PD) is one of the typical movement disorder diseases among elderly people, which has a serious impact on their daily lives. In this article, we propose a novel computation framework to recognize gait patterns in patients with...

Measuring Similarity Similarly: LDA and Human Perception
W. Ben Towne, Carolyn P. Rosé, James D. Herbsleb
Article No.: 7
DOI: 10.1145/2890510

Several intelligent technologies designed to improve navigability in and digestibility of text corpora use topic modeling such as the state-of-the-art Latent Dirichlet Allocation (LDA). This model and variants on it provide lower-dimensional...

CSM: A Cloud Service Marketplace for Complex Service Acquisition
Yexi Jiang, Chang-Shing Perng, Anca Sailer, Ignacio Silva-Lepe, Yang Zhou, Tao Li
Article No.: 8
DOI: 10.1145/2894759

The cloud service marketplace (CSM) is an exploratory project aiming to provide “an AppStore for Services.” It is an intelligent online marketplace that facilitates service discovery and acquisition for enterprise customers....

SPrank: Semantic Path-Based Ranking for Top-N Recommendations Using Linked Open Data
Tommaso Di Noia, Vito Claudio Ostuni, Paolo Tomeo, Eugenio Di Sciascio
Article No.: 9
DOI: 10.1145/2899005

In most real-world scenarios, the ultimate goal of recommender system applications is to suggest a short ranked list of items, namely top-N recommendations, that will appeal to the end user. Often, the problem of computing top-N...

A Unified Point-of-Interest Recommendation Framework in Location-Based Social Networks
Chen Cheng, Haiqin Yang, Irwin King, Michael R. Lyu
Article No.: 10
DOI: 10.1145/2901299

Location-based social networks (LBSNs), such as Gowalla, Facebook, Foursquare, Brightkite, and so on, have attracted millions of users to share their social friendship and their locations via check-ins in the past few years. Plenty of valuable...

Enhanced Knowledge-Leverage-Based TSK Fuzzy System Modeling for Inductive Transfer Learning
Zhaohong Deng, Yizhang Jiang, Hisao Ishibuchi, Kup-Sze Choi, Shitong Wang
Article No.: 11
DOI: 10.1145/2903725

The knowledge-leverage-based Takagi--Sugeno--Kang fuzzy system (KL-TSK-FS) modeling method has shown promising performance for fuzzy modeling tasks where transfer learning is required. However, the knowledge-leverage mechanism of the KL-TSK-FS can...

A Spatial-Temporal Topic Model for the Semantic Annotation of POIs in LBSNs
Tieke He, Hongzhi Yin, Zhenyu Chen, Xiaofang Zhou, Shazia Sadiq, Bin Luo
Article No.: 12
DOI: 10.1145/2905373

Semantic tags of points of interest (POIs) are a crucial prerequisite for location search, recommendation services, and data cleaning. However, most POIs in location-based social networks (LBSNs) are either tag-missing or tag-incomplete. This...

Dystemo: Distant Supervision Method for Multi-Category Emotion Recognition in Tweets
Valentina Sintsova, Pearl Pu
Article No.: 13
DOI: 10.1145/2912147

Emotion recognition in text has become an important research objective. It involves building classifiers capable of detecting human emotions for a specific application, for example, analyzing reactions to product launches, monitoring emotions at...

Driving Profiles Computation and Monitoring for Car Insurance CRM
Mirco Nanni, Roberto Trasarti, Anna Monreale, Valerio Grossi, Dino Pedreschi
Article No.: 14
DOI: 10.1145/2912148

Customer segmentation is one of the most traditional and valued tasks in customer relationship management (CRM). In this article, we explore the problem in the context of the car insurance industry, where the mobility behavior of customers...

Soft Confidence-Weighted Learning
Jialei Wang, Peilin Zhao, Steven C. H. Hoi
Article No.: 15
DOI: 10.1145/2932193

Online learning plays an important role in many big data mining problems because of its high efficiency and scalability. In the literature, many online learning algorithms using gradient information have been applied to solve online classification...