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Articles 5791 - 5820 of 9024
Full-Text Articles in Computer Sciences
Contract-Based General-Purpose Gpu Programming, Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz, Bertrand Meyer
Contract-Based General-Purpose Gpu Programming, Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz, Bertrand Meyer
Research Collection School Of Computing and Information Systems
Using GPUs as general-purpose processors has revolutionized parallel computing by offering, for a large and growing set of algorithms, massive data-parallelization on desktop machines. An obstacle to widespread adoption, however, is the difficulty of programming them and the low-level control of the hardware required to achieve good performance. This paper suggests a programming library, SafeGPU, that aims at striking a balance between programmer productivity and performance, by making GPU data-parallel operations accessible from within a classical object-oriented programming language. The solution is integrated with the design-by-contract approach, which increases confidence in functional program correctness by embedding executable program specifications into …
Privacy In Crowdsourced Platforms, Thivya Kandappu, Arik Friedman, Vijay Sivaraman, Roksana Boreli
Privacy In Crowdsourced Platforms, Thivya Kandappu, Arik Friedman, Vijay Sivaraman, Roksana Boreli
Research Collection School Of Computing and Information Systems
Emerging platforms, such as Amazon Mechanical Turk and Google Consumer Surveys, are increasingly being used by researchers and market analysts to crowdsource large-scale survey data from online populations at extremely low cost. However, by participating in successive surveys, workers risk being profiled and targeted, both by surveyors and by the platform itself. In this chapter we provide an overview of privacy in crowdsourcing platforms. We consider the state-of-the-art crowdsourcing platforms and the risks to worker privacy in such platforms, we survey the existing solutions, and later describe and evaluate the design of a privacy conscious crowdsourcing platform prototype, called Loki. …
Choosing Your Weapons: On Sentiment Analysis Tools For Software Engineering Research, Robbert Jongeling, Subhajit Datta, Alexander Serebrenik
Choosing Your Weapons: On Sentiment Analysis Tools For Software Engineering Research, Robbert Jongeling, Subhajit Datta, Alexander Serebrenik
Research Collection School Of Computing and Information Systems
Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact …
The Importance Of Being Isolated: An Empirical Study On Chromium Reviews, Subhajit Datta, Devarshi Bhatt, Manish Jain, Proshanta Sarkar, Santonu Sarkar
The Importance Of Being Isolated: An Empirical Study On Chromium Reviews, Subhajit Datta, Devarshi Bhatt, Manish Jain, Proshanta Sarkar, Santonu Sarkar
Research Collection School Of Computing and Information Systems
As large scale software development has become more collaborative, and software teams more globally distributed, several studies have explored how developer interaction influences software development outcomes. The emphasis so far has been largely on outcomes like defect count, the time to close modification requests etc. In the paper, we examine data from the Chromium project to understand how different aspects of developer discussion relate to the closure time of reviews. On the basis of analyzing reviews discussed by 2000+ developers, our results indicate that quicker closure of reviews owned by a developer relates to higher reception of information and insights …
Towards Automatic Generation Of Security-Centric Descriptions For Android Apps, Mu Zhang, Yue Duan, Qian Feng, Heng Yin
Towards Automatic Generation Of Security-Centric Descriptions For Android Apps, Mu Zhang, Yue Duan, Qian Feng, Heng Yin
Research Collection School Of Computing and Information Systems
To improve the security awareness of end users, Android markets directly present two classes of literal app information: 1) permission requests and 2) textual descriptions. Unfortunately, neither can serve the needs. A permission list is not only hard to understand but also inadequate; textual descriptions provided by developers are not security-centric and are significantly deviated from the permissions. To fill in this gap, we propose a novel technique to automatically generate security-centric app descriptions, based on program analysis. We implement a prototype system, DESCRIBEME, and evaluate our system using both DroidBench and real-world Android apps. Experimental results demonstrate that DESCRIBEME …
Inferring Door Locations From A Teammate's Trajectory In Stealth Human-Robot Team Operations, Jean Oh, Arne Suppe, Arne Suppe, Anthony Stentz, Martial Hebert
Inferring Door Locations From A Teammate's Trajectory In Stealth Human-Robot Team Operations, Jean Oh, Arne Suppe, Arne Suppe, Anthony Stentz, Martial Hebert
Research Collection School Of Computing and Information Systems
Robot perception is generally viewed as the interpretation of data from various types of sensors such as cameras. In this paper, we study indirect perception where a robot can perceive new information by making inferences from non-visual observations of human teammates. As a proof-of-concept study, we specifically focus on a door detection problem in a stealth mission setting where a team operation must not be exposed to the visibility of the team's opponents. We use a special type of the Noisy-OR model known as BN2O model of Bayesian inference network to represent the inter-visibility and to infer the locations of …
Endogenous Network Effects, Platform Pricing And Market Liquidity, Mei Lin, Ruhai Wu, Wen Zhou
Endogenous Network Effects, Platform Pricing And Market Liquidity, Mei Lin, Ruhai Wu, Wen Zhou
Research Collection School Of Computing and Information Systems
This paper examines a monopoly platform's two-sided pricing strategies in a setting with seller competition, which gives rise to not only positive cross-side network effects between buyers and sellers, but also a negative same-side network effect among sellers. We show that platform pricing depends crucially on the characteristics associated with market liquidity, which contrasts with the previous studies that point to the two sides' relative demand elasticities and/or network effects. A market is said to be more liquid when it has less friction, resulting in a larger total surplus for the platform economy and hence greater equilibrium entry on both …
Social Tag Relevance Estimation Via Ranking-Oriented Neighbour Voting, Chaoran Cui, Jialie Shen, Jun Ma, Tao Lian
Social Tag Relevance Estimation Via Ranking-Oriented Neighbour Voting, Chaoran Cui, Jialie Shen, Jun Ma, Tao Lian
Research Collection School Of Computing and Information Systems
User-generated tags associated with social images are frequently imprecise and incomplete. Therefore, a fundamental challenge in tag-based applications is the problem of tag relevance estimation, which concerns how to interpret and quantify the relevance of a tag with respect to the contents of an image. In this paper, we address the key problem from a new perspective of learning to rank, and develop a novel approach to facilitate tag relevance estimation to directly optimize the ranking performance of tag-based image search. A supervision step is introduced into the neighbour voting scheme, in which tag relevance is estimated by accumulating votes …
Mood Self-Assessment On Smartphones, Le Minh Khue, Eng Lieh Ouh, Stan Jarzabek
Mood Self-Assessment On Smartphones, Le Minh Khue, Eng Lieh Ouh, Stan Jarzabek
Research Collection School Of Computing and Information Systems
Mood has been systematically studied by psychologists for over 100 years. As mood is a subjective feeling, any study of mood must take into account and accurately capture user’s perception of an experienced feeling. In last 40 years, a number of pen-andpaper mood self-assessment scales have been proposed. Typically, a person is asked to separately rate various dimensions of the experienced feeling (e.g., pleasure and arousal) or mood items (interested, agitated, excited, etc.) on numeric scales (e.g., between 0 and 10). These partial ratings are then combined into an overall mood rating (or into its positive and negative affect). Penand-paper …
Enhancing Students' Learning Process Through Interactive Digital Media: New Opportunities For Collaborative Learning, Benjamin Gan, Thomas Menkhoff, Richard R. Smith
Enhancing Students' Learning Process Through Interactive Digital Media: New Opportunities For Collaborative Learning, Benjamin Gan, Thomas Menkhoff, Richard R. Smith
Research Collection School Of Computing and Information Systems
In this paper, we describe and review several examples of web technology-enabled teaching and learning approaches at undergraduate level in an Asian institution of higher learning. We begin by reporting on experiences made in the context of an iPad-enabled mobile learning project conducted during a Knowl- edge Management course (excursion) in support of the university’s technology-enabled learning vision. This is followed by reflections on the deployment of a collaborative social learning platform website (Edmodo), wiki- and web page-creation tools (Google Site), animated videos, etc. in elective courses on leadership and human capital management. Finally, we describe a proven project-based learning …
A Note On The Security Of Khl Scheme, Jian Weng, Yunlei Zhao, Deng, Robert H., Shengli Liu, Yanjiang Yang, Kouichi Sakurai
A Note On The Security Of Khl Scheme, Jian Weng, Yunlei Zhao, Deng, Robert H., Shengli Liu, Yanjiang Yang, Kouichi Sakurai
Research Collection School Of Computing and Information Systems
A public key trace and revoke scheme combines the functionality of broadcast encryption with the capability of traitor tracing. In Asiacrypt 2003, Kim, Hwang and Lee proposed a public key trace and revoke scheme (referred to as KHL scheme), and gave the security proof to support that their scheme is z-resilient against adaptive chosen-ciphertext attacks, in which the adversary is allowed to adaptively issue decryption queries as well as adaptively corrupt up to z users. In the passed ten years, KHL scheme has been believed as one of the most efficient public key trace and revoke schemes with z-resilience against …
Seeing Your Face Is Not Enough: An Inertial Sensor-Based Liveness Detection For Face Authentication, Yan Li, Yingjiu Li, Qiang Yan, Hancong Kong, Robert H. Deng
Seeing Your Face Is Not Enough: An Inertial Sensor-Based Liveness Detection For Face Authentication, Yan Li, Yingjiu Li, Qiang Yan, Hancong Kong, Robert H. Deng
Research Collection School Of Computing and Information Systems
Leveraging built-in cameras on smartphones and tablets, face authentication provides an attractive alternative of legacy passwords due to its memory-less authentication process. However, it has an intrinsic vulnerability against the media-based facial forgery (MFF) where adversaries use photos/videos containing victims' faces to circumvent face authentication systems. In this paper, we propose FaceLive, a practical and robust liveness detection mechanism to strengthen the face authentication on mobile devices in fighting the MFF-based attacks. FaceLive detects the MFF-based attacks by measuring the consistency between device movement data from the inertial sensors and the head pose changes from the facial video captured by …
Analyzing Educational Comments For Topics And Sentiments: A Text Analytics Approach, Gokran Ila Nitin, Swapna Gottipati, Venky Shankararaman
Analyzing Educational Comments For Topics And Sentiments: A Text Analytics Approach, Gokran Ila Nitin, Swapna Gottipati, Venky Shankararaman
Research Collection School Of Computing and Information Systems
Universities collect qualitative and quantitative feedback from students upon course completion in order to improve course quality and students’ learning experience. Combining program-wide and module-specific questions, universities collect feedback from students on three main aspects of a course namely, teaching style, content, and learning experience. The feedback is collected through both qualitative comments and quantitative scores. Current methods for analyzing the student course evaluations are manual and majorly focus on quantitative feedback and fall short of an in-depth exploration of qualitative feedback. In this paper, we develop student feedback mining system (SFMS) which applies text analytics and opinion mining approach …
Structural Constraints For Multipartite Entity Resolution With Markov Logic Network, Tengyuan Ye, Hady W. Lauw
Structural Constraints For Multipartite Entity Resolution With Markov Logic Network, Tengyuan Ye, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Multipartite entity resolution seeks to match entity mentions across several collections. An entity mention is presumed unique within a collection, and thus could match at most one entity mention in each of the other collections. In addition to domain-specific features considered in entity resolution, there are a number of domain-invariant structural contraints that apply in this scenario, including one-to-one assignment as well as cross-collection transitivity. We propose a principled solution to the multipartite entity resolution problem, building on the foundation of Markov Logic Network (MLN) that combines probabilistic graphical model and first-order logic. We describe how the domain-invariant structural constraints …
Targeted Blended Learning Through Competency Assessment In An Undergraduate Information Systems Program, Joelle Elmaleh, Shankararaman, Venky
Targeted Blended Learning Through Competency Assessment In An Undergraduate Information Systems Program, Joelle Elmaleh, Shankararaman, Venky
Research Collection School Of Computing and Information Systems
In this paper we report our study on the problem of competency acquisition when students progress from one course to another and more generally, from one term to the next. We observed that some students moved on to a second programming course without acquiring some of the competencies in the first programming course. This leads to problem in the second course, especially when these competencies are pre-requisites for this course. We applied blended learning, which allows a student to learn at least in part through delivery of content and instruction via online media, to overcome this problem. Our approach is …
Learning Relative Similarity From Data Streams: Active Online Learning Approaches, Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao
Learning Relative Similarity From Data Streams: Active Online Learning Approaches, Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao
Research Collection School Of Computing and Information Systems
Relative similarity learning, as an important learning scheme for information retrieval, aims to learn a bi-linear similarity function from a collection of labeled instance-pairs, and the learned function would assign a high similarity value for a similar instance-pair and a low value for a dissimilar pair. Existing algorithms usually assume the labels of all the pairs in data streams are always made available for learning. However, this is not always realistic in practice since the number of possible pairs is quadratic to the number of instances in the database, and manually labeling the pairs could be very costly and time …
Density Peaks Clustering Approach For Discovering Demand Hot Spots In City-Scale Taxi Fleet Dataset, Dongchang Liu, Shih-Fen Cheng, Yiping Yang
Density Peaks Clustering Approach For Discovering Demand Hot Spots In City-Scale Taxi Fleet Dataset, Dongchang Liu, Shih-Fen Cheng, Yiping Yang
Research Collection School Of Computing and Information Systems
In this paper, we introduce a variant of the density peaks clustering (DPC) approach for discovering demand hot spots from a low-frequency, low-quality taxi fleet operational dataset. From the literature, the DPC approach mainly uses density peaks as features to discover potential cluster centers, and this requires distances between all pairs of data points to be calculated. This implies that the DPC approach can only be applied to cases with relatively small numbers of data points. For the domain of urban taxi operations that we are interested in, we could have millions of demand points per day, and calculating all-pair …
Shineseniors: Personalized Services For Active Ageing-In-Place, Liming Bai, Alex I. Gavino, Wei Qi Lee, Jungyoon Kim, Na Liu, Hwee-Pink Tan, Hwee Xian Tan, Lee Buay Tan, Xiaoping Toh, Alvin Cerdena Valera, Elina Jia Yu, Alfred Wu, Mark S. Fox
Shineseniors: Personalized Services For Active Ageing-In-Place, Liming Bai, Alex I. Gavino, Wei Qi Lee, Jungyoon Kim, Na Liu, Hwee-Pink Tan, Hwee Xian Tan, Lee Buay Tan, Xiaoping Toh, Alvin Cerdena Valera, Elina Jia Yu, Alfred Wu, Mark S. Fox
Research Collection School Of Computing and Information Systems
Singapore faces a major challenge in providing care and support for senior citizens due to its rapidlyageing population and declining old-age support ratio. The concept of Ageing-in-Place was introduced by the Singapore government [1] to allow older people to live independently in their own homes and communities so that the need for institutionalised care will only be utilised when necessary. We have three fundamental questions that this project will answer: 1. How to make community care serviceseffective through innovations in care delivery? How to lower the cost of service delivery and improve 2. productivity of caregivers, by leveraging information and …
What Are The Characteristics Of High-Rated Apps? A Case Study On Free Android Applications, Tian Yuan, Meiyappan Nagappan, David Lo, Ahmed E. Hassan
What Are The Characteristics Of High-Rated Apps? A Case Study On Free Android Applications, Tian Yuan, Meiyappan Nagappan, David Lo, Ahmed E. Hassan
Research Collection School Of Computing and Information Systems
The tremendous rate of growth in the mobile app market over the past few years has attracted many developers to build mobile apps. However, while there is no shortage of stories of how lone developers have made great fortunes from their apps, the majority of developers are struggling to break even. For those struggling developers, knowing the “DNA” (i.e., characteristics) of high-rated apps is the first step towards successful development and evolution of their apps. In this paper, we investigate 28 factors along eight dimensions to understand how high-rated apps are different from low-rated apps. We also investigate what are …
Constrained Feature Selection For Localizing Faults, Tien-Duy B. Le, David Lo, Ming Li
Constrained Feature Selection For Localizing Faults, Tien-Duy B. Le, David Lo, Ming Li
Research Collection School Of Computing and Information Systems
Developers often take much time and effort to find buggy program elements. To help developers debug, many past studies have proposed spectrum-based fault localization techniques. These techniques compare and contrast correct and faulty execution traces and highlight suspicious program elements. In this work, we propose constrained feature selection algorithms that we use to localize faults. Feature selection algorithms are commonly used to identify important features that are helpful for a classification task. By mapping an execution trace to a classification instance and a program element to a feature, we can transform fault localization to the feature selection problem. Unfortunately, existing …
What's Hot In Software Engineering Twitter Space?, Abhishek Sharma, Tian Yuan, David Lo
What's Hot In Software Engineering Twitter Space?, Abhishek Sharma, Tian Yuan, David Lo
Research Collection School Of Computing and Information Systems
Twitter is a popular means to disseminate information and currently more than 300 million people are using it actively. Software engineers are no exception; Singer et al. have shown that many developers use Twitter to stay current with recent technological trends. At various time points, many users are posting microblogs (i.e., tweets) about the same topic in Twitter. We refer to this reasonably large set of topically-coherent microblogs in the Twitter space made at a particular point in time as an event. In this work, we perform an exploratory study on software engineering related events in Twitter. We collect a …
Smartphones And Ble Services: Empirical Insights, Meera Radhakrishnan, Archan Misra, Rajesh Krishna Balan, Youngki Lee
Smartphones And Ble Services: Empirical Insights, Meera Radhakrishnan, Archan Misra, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
Driven by the rapid market growth of sensors and beacons that offer Bluetooth Low Energy (BLE) based connectivity, this paper empirically investigates the performance characteristics of the BLE interface on multiple Android smartphones, and the consequent impact on a proposed BLE-based service: continuous indoor location. We first use extensive measurement studies with multiple Android devices to establish that the BLE interface on current smartphones is not as "low-energy" as nominally expected, and establish that continuous use of such a BLE interface is not feasible unless we choose a moderately large scan interval and a low duty cycle. We then explore …
Social Signal Processing For Real-Time Situational Understanding: A Vision And Approach, Kasthuri Jeyarajah, Shuchao Yao, Raghava Muthuraju, Archan Misra, Geeth De Mel, Julie Skipper, Tarek Abdelzaher, Michael Kolodny
Social Signal Processing For Real-Time Situational Understanding: A Vision And Approach, Kasthuri Jeyarajah, Shuchao Yao, Raghava Muthuraju, Archan Misra, Geeth De Mel, Julie Skipper, Tarek Abdelzaher, Michael Kolodny
Research Collection School Of Computing and Information Systems
The US Army Research Laboratory (ARL) and the Air Force Research Laboratory (AFRL) have established a collaborative research enterprise referred to as the Situational Understanding Research Institute (SURI). The goal is to develop an information processing framework to help the military obtain real-time situational awareness of physical events by harnessing the combined power of multiple sensing sources to obtain insights about events and their evolution. It is envisioned that one could use such information to predict behaviors of groups, be they local transient groups (e.g., protests) or widespread, networked groups, and thus enable proactive prevention of nefarious activities. This paper …
On Robust Image Spam Filtering Via Comprehensive Visual Modeling, Jialie Shen, Deng, Robert H., Zhiyong Cheng, Liqiang Nie, Shuicheng Yan
On Robust Image Spam Filtering Via Comprehensive Visual Modeling, Jialie Shen, Deng, Robert H., Zhiyong Cheng, Liqiang Nie, Shuicheng Yan
Research Collection School Of Computing and Information Systems
The Internet has brought about fundamental changes in the way peoples generate and exchange media information. Over the last decade, unsolicited message images (image spams) have become one of the most serious problems for Internet service providers (ISPs), business firms and general end users. In this paper, we report a novel system called RoBoTs (Robust BoosTrap based spam detector) to support accurate and robust image spam filtering. The system is developed based on multiple visual properties extracted from different levels of granularity, aiming to capture more discriminative contents for effective spam image identification. In addition, a resampling based learning framework …
Two Formulas For Success In Social Media: Learning And Network Effects, Liangfei Qiu, Qian Tang, Andrew B. Whinston
Two Formulas For Success In Social Media: Learning And Network Effects, Liangfei Qiu, Qian Tang, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
Recent years have witnessed an unprecedented explosion in information technology that enables dynamic diffusion of user-generated content in social networks. Online videos, in particular, have changed the landscape of marketing and entertainment, competing with premium content and spurring business innovations. In the present study, we examine how learning and network effects drive the diffusion of online videos. While learning happens through informational externalities, network effects are direct payoff externalities. Using a unique data set from YouTube, we empirically identify learning and network effects separately, and find that both mechanisms have statistically and economically significant effects on video views; furthermore, the …
Automated Prediction Of Bug Report Priority Using Multi-Factor Analysis, Yuan Tian, David Lo, Chengnian Sun, Xin Xia
Automated Prediction Of Bug Report Priority Using Multi-Factor Analysis, Yuan Tian, David Lo, Chengnian Sun, Xin Xia
Research Collection School Of Computing and Information Systems
Bugs are prevalent. To improve software quality, developers often allow users to report bugs that they found using a bug tracking system such as Bugzilla. Users would specify among other things, a description of the bug, the component that is affected by the bug, and the severity of the bug. Based on this information, bug triagers would then assign a priority level to the reported bug. As resources are limited, bug reports would be investigated based on their priority levels. This priority assignment process however is a manual one. Could we do better? In this paper, we propose an automated …
Should I Follow This Fault Localization Tool's Output? Automated Prediction Of Fault Localization Effectiveness, Tien-Duy B. Le, David Lo, Ferdian Thung
Should I Follow This Fault Localization Tool's Output? Automated Prediction Of Fault Localization Effectiveness, Tien-Duy B. Le, David Lo, Ferdian Thung
Research Collection School Of Computing and Information Systems
Debugging is a crucial yet expensive activity to improve the reliability of software systems. To reduce debugging cost, various fault localization tools have been proposed. A spectrum-based fault localization tool often outputs an ordered list of program elements sorted based on their likelihood to be the root cause of a set of failures (i.e., their suspiciousness scores). Despite the many studies on fault localization, unfortunately, however, for many bugs, the root causes are often low in the ordered list. This potentially causes developers to distrust fault localization tools. Recently, Parnin and Orso highlight in their user study that many debuggers …
Innovations In Financial Is And Technology Ecosystems: High-Frequency Trading Systems In The Equity Market, Robert J. Kauffman, Jun Liu, Dan Ma
Innovations In Financial Is And Technology Ecosystems: High-Frequency Trading Systems In The Equity Market, Robert J. Kauffman, Jun Liu, Dan Ma
Research Collection School Of Computing and Information Systems
Technology-based financial innovations over the past four decades have led to transformations in the financial markets. Understanding technological innovations in financial information systems (IS) and technologies has been challenging for technology consultants and financial industry practitioners due to the underlying complexities though. In this article, we propose an ecosystem analysis approach by extending the technology ecosystem paths of influence model (Adomavicius et al., 2008a) to incorporate stakeholder actions, considering both supply-side and demand-side forces for technological change. Our ecosystem model brings together three original core elements: technology components, technology-based services, and technology-supported business infrastructures. We also contribute a fourth new …
Enhancing Wifi-Based Localization With Visual Clues, Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, Yunhao Liu, Ke Yi
Enhancing Wifi-Based Localization With Visual Clues, Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, Yunhao Liu, Ke Yi
Research Collection School Of Computing and Information Systems
Indoor localization is of great importance to a wide range of applications in the era of mobile computing. Current mainstream solutions rely on Received Signal Strength (RSS) of wireless signals as fingerprints to distinguish and infer locations. However, those methods suffer from fingerprint ambiguity that roots in multipath fading and temporal dynamics of wireless signals. Though pioneer efforts have resorted to motion-assisted or peer-assisted localization, they neither work in real time nor work without the help of peer users, which introduces extra costs and constraints, and thus degrades their practicality. To get over these limitations, we propose Argus, an image-assisted …
Using Content-Level Structures For Summarizing Microblog Repost Trees, Jing Li, Wei Gao, Zhongyu Wei, Baolin Peng, Kam-Fai Wong
Using Content-Level Structures For Summarizing Microblog Repost Trees, Jing Li, Wei Gao, Zhongyu Wei, Baolin Peng, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
A microblog repost tree provides strong clues on how an event described therein develops. To help social media users capture the main clues of events on microblogging sites, we propose a novel repost tree summarization framework by effectively differentiating two kinds of messages on repost trees called leaders and followers, which are derived from contentlevel structure information, i.e., contents of messages and the reposting relations. To this end, Conditional Random Fields (CRF) model is used to detect leaders across repost tree paths. We then present a variant of random-walk-based summarization model to rank and select salient messages based on the …