Intelligent Systems and Technology (TIST)


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ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Diversity and Discovery in Recommender Systems, Online Advertising and Regular Papers, Volume 5 Issue 4, January 2015

Section: Special Section on Diversity and Discovery in Recommender Systems

Introduction to the Special Issue on Diversity and Discovery in Recommender Systems
Pablo Castells, Jun Wang, Rubén Lara, Dell Zhang
Article No.: 52
DOI: 10.1145/2668113

Multiobjective Pareto-Efficient Approaches for Recommender Systems
Marco Tulio Ribeiro, Nivio Ziviani, Edleno Silva De Moura, Itamar Hata, Anisio Lacerda, Adriano Veloso
Article No.: 53
DOI: 10.1145/2629350

Recommender systems are quickly becoming ubiquitous in applications such as e-commerce, social media channels, and content providers, among others, acting as an enabling mechanism designed to overcome the information overload problem by improving...

On Unexpectedness in Recommender Systems: Or How to Better Expect the Unexpected
Panagiotis Adamopoulos, Alexander Tuzhilin
Article No.: 54
DOI: 10.1145/2559952

Although the broad social and business success of recommender systems has been achieved across several domains, there is still a long way to go in terms of user satisfaction. One of the key dimensions for significant improvement is the concept of...

Diversifying Citation Recommendations
Onur Küçüktunç, Erik Saule, Kamer Kaya, Ümit V. Çatalyürek
Article No.: 55
DOI: 10.1145/2668106

Literature search is one of the most important steps of academic research. With more than 100,000 papers published each year just in computer science, performing a complete literature search becomes a Herculean task. Some of the existing...

Accurate and Novel Recommendations: An Algorithm Based on Popularity Forecasting
Amin Javari, Mahdi Jalili
Article No.: 56
DOI: 10.1145/2668107

Recommender systems are in the center of network science, and they are becoming increasingly important in individual businesses for providing efficient, personalized services and products to users. Previous research in the field of recommendation...

Section: Special Section on Online Advertising

Introduction to the Special Issue on Online Advertising
Dou Shen, Deepak Agarwal
Article No.: 57
DOI: 10.1145/2668123

Mining Mobile User Preferences for Personalized Context-Aware Recommendation
Hengshu Zhu, Enhong Chen, Hui Xiong, Kuifei Yu, Huanhuan Cao, Jilei Tian
Article No.: 58
DOI: 10.1145/2532515

Recent advances in mobile devices and their sensing capabilities have enabled the collection of rich contextual information and mobile device usage records through the device logs. These context-rich logs open a venue for mining the personal...

Location- and Query-Aware Modeling of Browsing and Click Behavior in Sponsored Search
Azin Ashkan, Charles L. A. Clarke
Article No.: 59
DOI: 10.1145/2534398

An online advertisement’s clickthrough rate provides a fundamental measure of its quality, which is widely used in ad selection strategies. Unfortunately, ads placed in contexts where they are rarely viewed—or where users are unlikely...

Sponsored Search Auctions: Recent Advances and Future Directions
Tao Qin, Wei Chen, Tie-Yan Liu
Article No.: 60
DOI: 10.1145/2668108

Sponsored search has been proven to be a successful business model, and sponsored search auctions have become a hot research direction. There have been many exciting advances in this field, especially in recent years, while at the same time, there...

Simple and Scalable Response Prediction for Display Advertising
Olivier Chapelle, Eren Manavoglu, Romer Rosales
Article No.: 61
DOI: 10.1145/2532128

Clickthrough and conversation rates estimation are two core predictions tasks in display advertising. We present in this article a machine learning framework based on logistic regression that is specifically designed to tackle the specifics of...

Real-Time Bid Optimization for Group-Buying Ads
Raju Balakrishnan, Rushi P. Bhatt
Article No.: 62
DOI: 10.1145/2532441

Group-buying ads seeking a minimum number of customers before the deal expiry are increasingly used by daily-deal providers. Unlike traditional web ads, the advertiser’s profits for group-buying ads depend on the time to expiry and...

Section: Regular Papers

Improved Approaches with Calibrated Neighboring Joint Density to Steganalysis and Seam-Carved Forgery Detection in JPEG Images
Qingzhong Liu, Zhongxue Chen
Article No.: 63
DOI: 10.1145/2560365

Steganalysis and forgery detection in image forensics are generally investigated separately. We have designed a method targeting the detection of both steganography and seam-carved forgery in JPEG images. We analyze the neighboring joint density...

Strategic Information Disclosure to People with Multiple Alternatives
Amos Azaria, Zinovi Rabinovich, Claudia V. Goldman, Sarit Kraus
Article No.: 64
DOI: 10.1145/2558397

In this article, we study automated agents that are designed to encourage humans to take some actions over others by strategically disclosing key pieces of information. To this end, we utilize the framework of persuasion games—a branch of...

Snap & Play: Auto-Generated Personalized Find-the-Difference Game
Si Liu, Qiang Chen, Shuicheng Yan, Changsheng Xu, Hanqing Lu
Article No.: 65
DOI: 10.1145/2668109

In this article, by taking a popular game, the Find-the-Difference (FiDi) game, as a concrete example, we explore how state-of-the-art image processing techniques can assist in developing a personalized, automatic, and dynamic game. Unlike the...

Choosing a Candidate Using Efficient Allocation of Biased Information
Shulamit Reches, Meir Kalech
Article No.: 66
DOI: 10.1145/2558327

This article deals with a decision-making problem concerning an agent who wants to choose a partner from multiple candidates for long-term collaboration. To choose the best partner, the agent can rely on prior information he knows about the...

Community Discovery from Social Media by Low-Rank Matrix Recovery
Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang
Article No.: 67
DOI: 10.1145/2668110

The pervasive usage and reach of social media have attracted a surge of attention in the multimedia research community. Community discovery from social media has therefore become an important yet challenging issue. However, due to the subjective...

Identifying Points of Interest Using Heterogeneous Features
Yiyang Yang, Zhiguo Gong, Leong Hou U
Article No.: 68
DOI: 10.1145/2668111

Deducing trip-related information from web-scale datasets has received large amounts of attention recently. Identifying points of interest (POIs) in geo-tagged photos is one of these problems. The problem can be viewed as a standard clustering...