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Articles 5341 - 5370 of 8479
Full-Text Articles in Computer Sciences
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 …
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 …
Scheduled Approximation For Personalized Pagerank With Utility-Based Hub Selection, Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying
Scheduled Approximation For Personalized Pagerank With Utility-Based Hub Selection, Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying
Research Collection School Of Computing and Information Systems
As Personalized PageRank has been widely leveraged for ranking on a graph, the efficient computation of Personalized PageRank Vector (PPV) becomes a prominent issue. In this paper, we propose FastPPV, an approximate PPV computation algorithm that is incremental and accuracy-aware. Our approach hinges on a novel paradigm of scheduled approximation: the computation is partitioned and scheduled for processing in an “organized” way, such that we can gradually improve our PPV estimation in an incremental manner and quantify the accuracy of our approximation at query time. Guided by this principle, we develop an efficient hub-based realization, where we adopt the metric …
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. …
Detect Rumors Using Time Series Of Social Context Information On Microblogging Websites, Jing Ma, Wei Gao, Zhongyu Wei, Yueming Lu, Kam-Fai Wong
Detect Rumors Using Time Series Of Social Context Information On Microblogging Websites, Jing Ma, Wei Gao, Zhongyu Wei, Yueming Lu, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Automatically identifying rumors from online social media especially microblogging websites is an important research issue. Most of existing work for rumor detection focuses on modeling features related to microblog contents, users and propagation patterns, but ignore the importance of the variation of these social context features during the message propagation over time. In this study, we propose a novel approach to capture the temporal characteristics of these features based on the time series of rumor's lifecycle, for which time series modeling technique is applied to incorporate various social context information. Our experiments using the events in two microblog datasets confirm …
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 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 …
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 …
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 …
Assessing Developer Contribution With Repository Mining-Based Metrics, Jalerson Lima, Christoph Treude, Fernando Figueira Filho, Uirá Kulesza
Assessing Developer Contribution With Repository Mining-Based Metrics, Jalerson Lima, Christoph Treude, Fernando Figueira Filho, Uirá Kulesza
Research Collection School Of Computing and Information Systems
Productivity as a result of individual developers' contributions is an important aspect for software companies to maintain their competitiveness in the market. However, there is no consensus in the literature on how to measure productivity or developer contribution. While some repository mining-based metrics have been proposed, they lack validation in terms of their applicability and usefulness from the individuals who will use them to assess developer contribution: team and project leaders. In this paper, we propose the design of a suite of metrics for the assessment of developer contribution, based on empirical evidence obtained from project and team leaders. In …
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 …
Trace Element Composition Of Pm2.5 And Pm10 From Kolkata - A Heavily Polluted Indian Metropolis, Reshmi Das, Bahareh Khezri, Bijayen Srivastava, Subhajit Datta, Pradip Kumar Sikdar, Richard D. Webster, Xianfeng Wang
Trace Element Composition Of Pm2.5 And Pm10 From Kolkata - A Heavily Polluted Indian Metropolis, Reshmi Das, Bahareh Khezri, Bijayen Srivastava, Subhajit Datta, Pradip Kumar Sikdar, Richard D. Webster, Xianfeng Wang
Research Collection School Of Computing and Information Systems
Elemental composition of PM2.5 and PM10 was measured from 16 locations in Greater Kolkata in Eastern India. Sampling was carried out in the winter months of 2013–2014. PM2.5 and PM10 mass concentrations ranged from 83–783 μg/m3 and 167–928 μg/m3 respectively. 20 elements were measured with an Agilent 7700 series ICP–MS equipped with a 3rd generation He reaction/collision cell following closed vessel microwave digestion. In both size fractions Fe, Na, Al, K, Ca were present in high concentrations (>1 000 ng/m3), Mn, Zn and Pb demonstrated medium concentrations (>100 ng/m …
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 …
Event And Strategy Analytics, Jin Song Dong, Jun Sun, Yang Liu, Yuan-Fang Li, Jing Sun, Ling Shi
Event And Strategy Analytics, Jin Song Dong, Jun Sun, Yang Liu, Yuan-Fang Li, Jing Sun, Ling Shi
Research Collection School Of Computing and Information Systems
Model checking has been pervasive and successful in finding bugs in hardware and software systems, including real-time and probabilistic systems. Applying model checking to decision making is relative new and has an excellent potential to be compliment to data analytics and other Artificial Intelligent (AI) or Operational Research (OR) based decision making techniques. Our last 8 years research has focused on the development of PAT (Process Analysis Toolkit) [18] which supports modelling languages that combine the expressiveness of event, state, time and probability based modeling techniques to which model checking can be directly applied. The next direction for PAT is …
Maximum Rank Query, Kyriakos Mouratidis, Jilian Zhang, Hwee Hwa Pang
Maximum Rank Query, Kyriakos Mouratidis, Jilian Zhang, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
The top-k query is a common means to shortlist a number of options from a set of alternatives, based on the user's preferences. Typically, these preferences are expressed as a vector of query weights, defined over the options' attributes. The query vector implicitly associates each alternative with a numeric score, and thus imposes a ranking among them. The top-k result includes the k options with the highest scores. In this context, we define the maximum rank query (MaxRank). Given a focal option in a set of alternatives, the MaxRank problem is to compute the highest rank this option may achieve …
Tagcombine: Recommending Tags To Contents In Software Information Sites, Xin Yu Wang, Xin Xia, David Lo
Tagcombine: Recommending Tags To Contents In Software Information Sites, Xin Yu Wang, Xin Xia, David Lo
Research Collection School Of Computing and Information Systems
Nowadays, software engineers use a variety of online media to search and become informed of new and interesting technologies, and to learn from and help one another. We refer to these kinds of online media which help software engineers improve their performance in software development, maintenance, and test processes as software information sites. In this paper, we propose TagCombine, an automatic tag recommendation method which analyzes objects in software information sites. TagCombine has three different components: 1) multi-label ranking component which considers tag recommendation as a multi-label learning problem; 2) similarity-based ranking component which recommends tags from similar objects; 3) …
On Security Of Content-Based Video Stream Authentication, Swee Won Lo, Zhou Wei, Deng, Robert H., Xuhua Ding
On Security Of Content-Based Video Stream Authentication, Swee Won Lo, Zhou Wei, Deng, Robert H., Xuhua Ding
Research Collection School Of Computing and Information Systems
Content-based authentication (CBA) schemes are used to authenticate multimedia streams while allowing content-preserving manipulations such as bit-rate transcoding. In this paper, we survey and classify existing transform-domain CBA schemes for videos into two categories, and point out that in contrary to CBA for images, there exists a common design flaw in these schemes. We present the principles (based on video coding concept) on how the flaw can be exploited to mount semantic-changing attacks in the transform domain that cannot be detected by existing CBA schemes. We show attack examples including content removal, modification and insertion attacks. Noting that these CBA …
Server-Aided Revocable Identity-Based Encryption, Baodong Qin, Deng, Robert H., Yingjiu Li, Shengli Liu
Server-Aided Revocable Identity-Based Encryption, Baodong Qin, Deng, Robert H., Yingjiu Li, Shengli Liu
Research Collection School Of Computing and Information Systems
Efficient user revocation in Identity-Based Encryption (IBE) has been a challenging problem and has been the subject of several research efforts in the literature. Among them, the tree-based revocation approach, due to Boldyreva, Goyal and Kumar, is probably the most efficient one. In this approach, a trusted Key Generation Center (KGC) periodically broadcasts a set of key updates to all (non-revoked) users through public channels, where the size of key updates is only O(r log N/r), with N being the number of users and r the number of revoked users, respectively; however, every user needs to keep at least O(logN) …
Answering Why-Not Questions On Reverse Top-K Queries, Yunjun Gao, Qing Liu, Gang Chen, Baihua Zheng, Linlin Zhou
Answering Why-Not Questions On Reverse Top-K Queries, Yunjun Gao, Qing Liu, Gang Chen, Baihua Zheng, Linlin Zhou
Research Collection School Of Computing and Information Systems
Why-not questions, which aim to seek clarifications on the missing tuples for query results, have recently received considerable attention from the database community. In this paper, we systematically explore why-not questions on reverse top-k queries, owing to its importance in multi-criteria decision making. Given an initial reverse top-k query and a missing/why-not weighting vector set Wm that is absent from the query result, why-not questions on reverse top-k queries explain why Wm does not appear in the query result and provide suggestions on how to refine the initial query with minimum penalty to include Wm in the refined query result. …
Evaluation And Improvement Of Procurement Process With Data Analytics, Melvin H. C. Tan, Wee Leong Lee
Evaluation And Improvement Of Procurement Process With Data Analytics, Melvin H. C. Tan, Wee Leong Lee
Research Collection School Of Computing and Information Systems
Analytics can be applied in procurement to benefit organizations beyond just prevention and detection of fraud. This study aims to demonstrate how advanced data mining techniques such as text mining and cluster analysis can be used to improve visibility of procurement patterns and provide decision-makers with insight to develop more efficient sourcing strategies, in terms of cost and effort. A case study of an organization’s effort to improve its procurement process is presented in this paper. The findings from this study suggest that opportunities exist for organizations to aggregate common goods and services among the purchases made under and across …
Towards Opinion Summarization From Online Forums, Ding Ying, Jing Jiang
Towards Opinion Summarization From Online Forums, Ding Ying, Jing Jiang
Research Collection School Of Computing and Information Systems
Summarizing opinions expressed in online forums can potentially benefit many people. However, special characteristics of this problem may require changes to standard text summarization techniques. In this work, we present our initial attempt at extractive summarization of opinionated online forum threads. Given the nature of user generated content in online discussion forums, we hypothesize that besides relevance, text quality and subjectivity also play important roles in deciding which sentences are good summary sentences. We therefore construct an annotated corpus to facilitate our study of extractive summarization of online discussion forums. We define a set of features to capture relevance, text …
A Joint Model Of Product Properties, Aspects And Ratings For Online Reviews, Ding Ying, Jing Jiang
A Joint Model Of Product Properties, Aspects And Ratings For Online Reviews, Ding Ying, Jing Jiang
Research Collection School Of Computing and Information Systems
Product review mining is an important task that can benefit both businesses and consumers. Lately a number of models combining collaborative filtering and content analysis to model reviews have been proposed, among which the Hidden Factors as Topics (HFT) model is a notable one. In this work, we propose a new model on top of HFT to separate product properties and aspects. Product properties are intrinsic to certain products (e.g. types of cuisines of restaurants) whereas aspects are dimensions along which products in the same category can be compared (e.g. service quality of restaurants). Our proposed model explicitly separates the …
Information Retrieval And Spectrum Based Bug Localization: Better Together, Tien-Duy B. Le, Richard J. Oentaryo, David Lo
Information Retrieval And Spectrum Based Bug Localization: Better Together, Tien-Duy B. Le, Richard J. Oentaryo, David Lo
Research Collection School Of Computing and Information Systems
Debugging often takes much effort and resources. To help developers debug, numerous information retrieval (IR)-based and spectrum-based bug localization techniques have been proposed. IR-based techniques process textual information in bug reports, while spectrum-based techniques process program spectra (i.e., a record of which program elements are executed for each test case). Both eventually generate a ranked list of program elements that are likely to contain the bug. However, these techniques only consider one source of information, either bug reports or program spectra, which is not optimal. To deal with the limitation of existing techniques, in this work, we propose a new …
How Practitioners Perceive The Relevance Of Software Engineering Research, David Lo, Nachiappan Nagappan, Thomas Zimmermann
How Practitioners Perceive The Relevance Of Software Engineering Research, David Lo, Nachiappan Nagappan, Thomas Zimmermann
Research Collection School Of Computing and Information Systems
The number of software engineering research papers over the last few years has grown significantly. An important question here is: how relevant is software engineering research to practitioners in the field? To address this question, we conducted a survey at Microsoft where we invited 3,000 industry practitioners to rate the relevance of research ideas contained in 571 ICSE, ESEC/FSE and FSE papers that were published over a five year period. We received 17,913 ratings by 512 practitioners who labelled ideas as essential, worthwhile, unimportant, or unwise. The results from the survey suggest that practitioners are positive towards studies done by …
Did You Expect Your Users To Say This?: Distilling Unexpected Micro-Reviews For Venue Owners, Wen-Haw Chong, Bingtian Dai, Ee-Peng Lim
Did You Expect Your Users To Say This?: Distilling Unexpected Micro-Reviews For Venue Owners, Wen-Haw Chong, Bingtian Dai, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
With social media platforms such as Foursquare, users can now generate concise reviews, i.e. micro-reviews, about entities such as venues (or products). From the venue owner's perspective, analysing these micro-reviews will offer interesting insights, useful for event detection and customer relationship management. However not all micro-reviews are equally important, especially since a venue owner should already be familiar with his venue's primary aspects. Instead we envisage that a venue owner will be interested in micro-reviews that are unexpected to him. These can arise in many ways, such as users focusing on easily overlooked aspects (by the venue owner), making comparisons …
Latent Factors Meet Homophily In Diffusion Modelling, Duc Minh Luu, Ee-Peng Lim
Latent Factors Meet Homophily In Diffusion Modelling, Duc Minh Luu, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Diffusion is an important dynamics that helps spreading information within an online social network. While there are already numerous models for single item diffusion, few have studied diffusion of multiple items, especially when items can interact with one another due to their inter-similarity. Moreover, the well-known homophily effect is rarely considered explicitly in the existing diffusion models. This work therefore fills this gap by proposing a novel model called Topic level Interaction Homophily Aware Diffusion (TIHAD) to include both latent factor level interaction among items and homophily factor in diffusion. The model determines item interaction based on latent factors and …