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Using Micro-Reviews To Select An Efficient Set Of Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Using Micro-Reviews To Select An Efficient Set Of Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Research Collection School Of Computing and Information Systems
Online reviews are an invaluable resource for web users trying to make decisions regarding products or services. However, the abundance of review content, as well as the unstructured, lengthy, and verbose nature of reviews make it hard for users to locate the appropriate reviews, and distill the useful information. With the recent growth of social networking and micro-blogging services, we observe the emergence of a new type of online review content, consisting of bite-sized, 140 character-long reviews often posted reactively on the spot via mobile devices. These micro-reviews are short, concise, and focused, nicely complementing the lengthy, elaborate, and verbose …
Tesla: An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Burcin Becerik-Gerber, Milind Tambe
Tesla: An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Burcin Becerik-Gerber, Milind Tambe
Research Collection School Of Computing and Information Systems
This innovative application paper presents TESLA, an agent-based application for optimizing the energy use in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. TESLA provides three key contributions: (i) three online scheduling algorithms that consider flexibility of people’s preferences for energyefficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; and (iii) surveys of real users that indicate that TESLA’s assumptions exist in practice. TESLA was evaluated on data of over 110,000 meetings held …
Roundtriprank: Graph-Based Proximity With Importance And Specificity, Yuan Fang, Kevin Chen-Chuan Chang, Hady W. Lauw
Roundtriprank: Graph-Based Proximity With Importance And Specificity, Yuan Fang, Kevin Chen-Chuan Chang, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Graph-based proximity has many applications with different ranking needs. However, most previous works only stress the sense of importance by finding "popular” results for a query. Often times important results are overly general without being well-tailored to the query, lacking a sense of specificity— which only emerges recently. Even then, the two senses are treated independently, and only combined empirically. In this paper, we generalize the well-studied importance-based random walk into a round trip and develop RoundTripRank, seamlessly integrating specificity and importance in one coherent process. We also recognize the need for a flexible trade-off between the two senses, and …
Modeling And Verifying Hierarchical Real-Time Systems Using Stateful Timed Csp, Jun Sun, Yang Liu, Jin Song Dong, Yan Liu, Ling Shi, Étienne André
Modeling And Verifying Hierarchical Real-Time Systems Using Stateful Timed Csp, Jun Sun, Yang Liu, Jin Song Dong, Yan Liu, Ling Shi, Étienne André
Research Collection School Of Computing and Information Systems
Modeling and verifying complex real-time systems are challenging research problems. The de facto approach is based on Timed Automata, which are finite state automata equipped with clock variables. Timed Automata are deficient in modeling hierarchical complex systems. In this work, we propose a language called Stateful Timed CSP and an automated approach for verifying Stateful Timed CSP models. Stateful Timed CSP is based on Timed CSP and is capable of specifying hierarchical real-time systems. Through dynamic zone abstraction, finite-state zone graphs can be generated automatically from Stateful Timed CSP models, which are subject to model checking. Like Timed Automata, Stateful …
Multimedia Recommendation: Technology And Techniques, Jialie Shen, Meng Wang, Shuicheng Yan, Peng Cui
Multimedia Recommendation: Technology And Techniques, Jialie Shen, Meng Wang, Shuicheng Yan, Peng Cui
Research Collection School Of Computing and Information Systems
In recent years, we have witnessed a rapid growth in the availability of digital multimedia on various application platforms and domains. Consequently, the problem of information overload has become more and more serious. In order to tackle the challenge, various multimedia recommendation technologies have been developed by different research communities (e.g., multimedia systems, information retrieval, machine learning and computer version). Meanwhile, many commercial web systems (e.g., Flick, YouTube, and Last.fm) have successfully applied recommendation techniques to provide users personalized content and services in a convenient and flexible way. When looking back, the information retrieval (IR) community has a long history …