Communication Commons^™

Overview Of Contrast Data Mining As A Field And Preview Of An Upcoming Book, Guozhu Dong, James Bailey

Kno.e.sis Publications

This report provides an overview of the field of contrast data mining and its applications, and offers a preview of an upcoming book on the topic. The importance of contrasting is discussed and a brief survey is given covering the following topics: general definitions and terminology for contrast patterns, representative contrast pattern mining algorithms, applications of contrast mining for fundamental data mining tasks such as classification and clustering, applications of contrast mining in bioinformatics, medicine, blog analysis, image analysis and subgroup mining, results on contrast based dataset similarity measure, and on analyzing item interaction in contrast patterns, and open research …

Computing Inconsistency Measure Based On Paraconsistent Semantics, Pascal Hitzler, Yue Ma, Guilin Qi

Computer Science and Engineering Faculty Publications

Measuring inconsistency in knowledge bases has been recognized as an important problem in several research areas. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. However, existing methods suffer from two limitations: (i) they are mostly restricted to propositional knowledge bases; (ii) very few of them discuss computational aspects of computing inconsistency measures. In this article, we try to solve these two limitations by exploring algorithms for computing an inconsistency measure of first-order knowledge bases. After introducing a four-valued semantics for first-order logic, we define an …

Modeling Social Strength In Social Media Community Via Kernel-Based Learning, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Xian-Sheng Hua, Shipeng Li

Research Collection School Of Computing and Information Systems

Modeling continuous social strength rather than conventional binary social ties in the social network can lead to a more precise and informative description of social relationship among people. In this paper, we study the problem of social strength modeling (SSM) for the users in a social media community, who are typically associated with diverse form of data. In particular, we take Flickr---the most popular online photo sharing community---as an example, in which users are sharing their experiences through substantial amounts of multimodal contents (e.g., photos, tags, geo-locations, friend lists) and social behaviors (e.g., commenting and joining interest groups). Such heterogeneous …

Context-Based Friend Suggestion In Online Photo-Sharing Community, Ting Yao, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

With the popularity of social media, web users tend to spend more time than before for sharing their experience and interest in online photo-sharing sites. The wide variety of sharing behaviors generate different metadata which pose new opportunities for the discovery of communities. We propose a new approach, named context-based friend suggestion, to leverage the diverse form of contextual cues for more effective friend suggestion in the social media community. Different from existing approaches, we consider both visual and geographical cues, and develop two user-based similarity measurements, i.e., visual similarity and geo similarity for characterizing user relationship. The problem of …

Wsm 2011: Third Acm Workshop On Social Media, Steven C. H. Hoi, Michal Jacovi, Ioannis Kompatsiaris, Jiebo Luo, Konstantinos Tserpes

Research Collection School Of Computing and Information Systems

The Third Workshop on Social Media (WSM2011) continues the series of Workshops on Social Media in 2009 and 2010 and has been established as a platform for the presentation and discussion of the latest, key research issues in social media analysis, exploration, search, mining, and emerging new social media applications. It is held in conjunction with the ACM International Multimedia Conference (MM'11) at Scottsdale, Arizona, USA, 2011 and has attracted contributions on various aspects of social media including data mining from social media, content organization, geo-localization, personalization, recommendation systems, user experience, machine learning and social media approaches and architectures for …

Mining Interesting Link Formation Rules In Social Networks, Cane Wing-Ki Leung, Ee Peng Lim, David Lo, Jianshu Weng

David LO

Link structures are important patterns one looks out for when modeling and analyzing social networks. In this paper, we propose the task of mining interesting Link Formation rules (LF-rules) containing link structures known as Link Formation patterns (LF-patterns). LF-patterns capture various dyadic and/or triadic structures among groups of nodes, while LF-rules capture the formation of a new link from a focal node to another node as a postcondition of existing connections between the two nodes. We devise a novel LF-rule mining algorithm, known as LFR-Miner, based on frequent subgraph mining for our task. In addition to using a support-confidence framework …

Coping With Distance: An Empirical Study Of Communication On The Jazz Platform, Renuka Sindhgatta, Bikram Sengupta, Subhajit Datta

Research Collection School Of Computing and Information Systems

Global software development - which is characterized by teams separated by physical distance and/or time-zone differences - has traditionally posed significant communication challenges. Often these have caused delays in completing tasks, or created misalignment across sites leading to re-work. In recent years, however, a new breed of development environments with rich collaboration features have emerged to facilitate cross-site work in distributed projects. In this paper we revisit the question "does distance matter?" in the context of IBM Jazz Platform -- a state-of-the-art collaborative development environment. We study the ecosystem of a large distributed team of around 300 members across 35 …

The Knowledge-Driven Exploration Of Integrated Biomedical Knowledge Sources Facilitates The Generation Of New Hypotheses, Vinh Nguyen, Olivier Bodenreider, Todd Minning, Amit P. Sheth

Kno.e.sis Publications

Knowledge gained from the scientific literature can complement newly obtained experimental data in helping researchers understand the pathological processes underlying diseases. However, unless the scientific literature and experimental data are semantically integrated, it is generally difficult for scientists to exploit the two sources effectively. We argue that, in addition to the semantic integration of heterogeneous knowledge sources, the usability of the integrated resource by scientists is dependent upon the availability of knowledge visualization and exploration tools. Moreover, the integration techniques must be scalable and the exploration interfaces must be easy to use by bench scientists. The end goal of such …

Demonstration: Real-Time Semantic Analysis Of Sensor Streams, Harshal Patni, Cory Andrew Henson, Michael Cooney, Amit P. Sheth, Krishnaprasad Thirunarayan

Kno.e.sis Publications

The emergence of dynamic information sources – including sensor networks – has led to large streams of real-time data on the Web. Research studies suggest, these dynamic networks have created more data in the last three years than in the entire history of civilization, and this trend will only increase in the coming years [1]. With this coming data explosion, real-time analytics software must either adapt or die [2]. This paper focuses on the task of integrating and analyzing multiple heterogeneous streams of sensor data with the goal of creating meaningful abstractions, or features. These features are then temporally aggregated …

Demonstration: Secure - Semantics Empowered Rescue Environment, Pratikkumar Desai, Cory Andrew Henson, Pramod Anantharam, Amit P. Sheth

Kno.e.sis Publications

This paper demonstrates a Semantic Web enabled system for collecting and processing sensor data within a rescue environment. The real-time system collects heterogeneous raw sensor data from rescue robots through a wireless sensor network. The raw sensor data is converted to RDF using the Semantic Sensor Network (SSN) ontology and further processed to generate abstractions used for event detection in emergency scenarios.

Identifying Social Influence In Networks Using Randomized Experiments, Sinan Aral, Dylan Walker

Business Faculty Articles and Research

The recent availability of massive amounts of networked data generated by email, instant messaging, mobile phone communications, micro blogs, and online social networks is enabling studies of population-level human interaction on scales orders of magnitude greater than what was previously possible.1'2 One important goal of applying statistical inference techniques to large networked datasets is to understand how behavioral contagions spread in human social networks. More precisely, understanding how people influence or are influenced by their peers can help us understand the ebb and flow of market trends, product adoption and diffusion, the spread of health behaviors such as smoking and …

Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng

Research Collection School Of Computing and Information Systems

Social networking has grown rapidly over the last few years, and social networks contain a huge amount of content. However, it can be not easy to navigate the social networks to find specific information. In this paper, we define a new type of queries, namely context-aware nearest neighbor (CANN) search over social network to retrieve the nearest node to the query node that matches the context specified. CANN considers both the structure of the social network, and the profile information of the nodes. We design ahyper-graph based index structure to support approximated CANN search efficiently.

On Modeling Virality Of Twitter Content, Tuan Anh Hoang, Ee Peng Lim, Palakorn Achananuparp, Jing Jiang, Feida Zhu

Research Collection School Of Computing and Information Systems

Twitter is a popular microblogging site where users can easily use mobile phones or desktop machines to generate short messages to be shared with others in realtime. Twitter has seen heavy usage in many recent international events including Japan earthquake, Iran election, etc. In such events, many tweets may become viral for different reasons. In this paper, we study the virality of socio-political tweet content in the Singapore’s 2011 general election (GE2011). We collected tweet data generated by about 20K Singapore users from 1 April 2011 till 12 May 2011, and the follow relationships among them. We introduce several quantitative …

Sempush: Privacy-Aware And Scalable Broadcasting For Semantic Microblogging, Pavan Kapanipathi, Julia Anaya, Alexandre Passant

Kno.e.sis Publications

Users of traditional microblogging platforms such as Twitter face drawbacks in terms of (1) Privacy of status updates as a followee - reaching undesired people (2) Information overload as a follower - receiving uninteresting microposts from followees. In this paper we demonstrate distributed and user-controlled dissemination of microposts using SMOB (semantic microblogging framework) and Semantic Hub (privacy-aware implementation of PuSH3 protocol) . The approach leverages users' Social Graph to dynamically create group of followers who are eligible to receive micropost. The restrictions to create the groups are provided by the followee based on the hastags in the micropost. Both SMOB …

A Domain Specific Language For Enterprise Grade Cloud-Mobile Hybrid Applications, Ajith H. Ranabahu, E. Michael Maximilien, Amit P. Sheth, Krishnaprasad Thirunarayan

Kno.e.sis Publications

Cloud computing has changed the technology landscape by offering flexible and economical computing resources to the masses. However, vendor lock-in makes the migration of applications and data across clouds an expensive proposition. The lock-in is especially serious when considering the new technology trend of combining cloud with mobile devices.

In this paper, we present a domain specific language (DSL) that is purposely created for generating hybrid applications spanning across mobile devices as well as computing clouds. We propose a model-driven development process that makes use of a DSL to provide sufficient programming abstractions over both cloud and mobile features. We …

Semantic Annotation And Search For Resources In The Next Generation Web With Sa-Rest, Ajith H. Ranabahu, Amit P. Sheth, Maryam Panahiazar, Sanjaya Wijeratne

Kno.e.sis Publications

SA-REST, the W3C member submission, can be used for supporting a wide variety of Plain Old Semantic HTML (POSH) annotation capabilities on any type of Web resource. Kino framework and tools provide support of capabilities to realize SA-RESTs promised value. These tools include (a) a browser-plugin to support annotation of a Web resource (including services) with respect to an ontology, domain model or vocabulary, (b) an annotation aware indexing engine and (c) faceted search and selection of the Web resources. At one end of the spectrum, we present Kino^E (aka Kino for Enterprise) which uses NCBO formal ontologies and …

Personalized Filtering Of The Twitter Stream, Pavan Kapanipathi, Fabrizio Orlandi, Amit P. Sheth, Alexandre Passant

Kno.e.sis Publications

With the rapid growth in users on social networks, there is a corresponding increase in user-generated content, in turn resulting in information overload. On Twitter, for example, users tend to receive uninterested information due to their non-overlapping interests from the people whom they follow. In this paper we present a Semantic Web approach to filter public tweets matching interests from personalized user profiles. Our approach includes automatic generation of multi-domain and personalized user profiles, filtering Twitter stream based on the generated profiles and delivering them in real-time. Given that users interests and personalization needs change with time, we also discuss …

Mining Direct Antagonistic Communities In Explicit Trust Networks, David Lo, Didi Surian, Zhang Kuan, Ee Peng Lim

Research Collection School Of Computing and Information Systems

There has been a recent increase of interest in analyzing trust and friendship networks to gain insights about relationship dynamics among users. Many sites such as Epinions, Facebook, and other social networking sites allow users to declare trusts or friendships between different members of the community. In this work, we are interested in extracting direct antagonistic communities (DACs) within a rich trust network involving trusts and distrusts. Each DAC is formed by two subcommunities with trust relationships among members of each sub-community but distrust relationships across the sub-communities. We develop an efficient algorithm that could analyze large trust networks leveraging …

A Survey Of Information Diffusion Models And Relevant Problems, Minh Duc Luu, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

There has been tremendous interest in diffusion of innovations or information in a social system. Nowadays, social networks (offline as well as online) are considered as important medium for diffusion and large amount of research has been conducted to understand the dynamics of diffusion in social networks. In this work, we review some of the models proposed for diffusion in social networks. We also highlight the major features of these models by dividing the surveyed models into two categories: non-network and network diffusion models. The former refers to user communities without any knowledge about the user relationship network and the …

Semantic Computing In Real-World: Vertical And Horizontal Application Within Enterprise And On The Web, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Kino: A Generic Document Management System For Biologists Using Sa-Rest And Faceted Search, Ajith Harshana Ranabahu, Priti Parikh, Maryam Panahiazar, Amit P. Sheth

Kno.e.sis Publications

Document management has become an important consideration for the scientific community over the last decade. Human knowledge is central to many scientific domains, thus it is not possible to completely automate the document management process. Managing scientific documents require a semi-automatic approach to overcome issues of large volume, yet support the human participation in the process. In this paper we present Kino, a set of tools that streamline the document management process in life science domains. Kino is integrated with National Center for Biomedical Ontology (NCBO), providing scientists access to quality domain models. Annotated documents are indexed using a faceted …

Citizen Sensing: Opportunities And Challenges In Mining Social Signals And Perceptions, Amit P. Sheth

Kno.e.sis Publications

Millions of persons have become 'citizens' of an Internet- or Web-enabled social community. Web 2.0 fostered the open environment and applications for tagging, blogging, wikis, and social networking sites that have made information consumption, production, and sharing so incredibly easy. An interconnected network of people who actively observe, report, collect, analyze, and disseminate information via text, audio, or video messages, increasingly through pervasively connected mobile devices, has led to what we term citizen sensing. In this talk, we review recent progress in supporting collective intelligence through intelligent processing of citizen sensing. Key issues we cover in this talk are: - …

Local Closed World Semantics: Keep It Simple, Stupid!, Adila Krishnadhi, Kunal Sengupta, Pascal Hitzler

Computer Science and Engineering Faculty Publications

A combination of open and closed-world reasoning (usually called local closed world reasoning) is a desirable capability of knowledge representation formalisms for Semantic Web applications. However, none of the proposals made to date for extending description logics with local closed world capabilities has had any significant impact on applications. We believe that one of the key reasons for this is that current proposals fail to provide approaches which are intuitively accessible for application developers at the same time are applicable, as extensions, to expressive description logics as SROIQ, which underlies the Web Ontology Language OWL.

In this paper, we propose …

Web Wisdom: An Essay On How Web 2.0 And Semantic Web Can Foster A Global Knowledge Society, Christopher Thomas, Amit P. Sheth

Kno.e.sis Publications

Admittedly this is a presumptuous title that should never be used when reporting on individual research advances. Wisdom is just not a scientific concept. In this case, though, we are reporting on recent developments on the web that lead us to believe that the web is on the way to providing a platform for not only information acquisition and business transactions but also for large scale knowledge development and decision support. It is likely that by now every web user has participated in some sort of social function or knowledge accumulating function on the web, many times without even being …

Smob: The Best Of Both Worlds, Alexandre Passant, Julia Anaya, Owen Sacco, Pavan Kapanipathi

Kno.e.sis Publications

This paper presents the architecture of SMOB and the way it combines Semantic Web standards (RDF(S) / SPARQL) and new protocols such as PubSubHubbub to enable a Federated and Privacy-Aware Social Web.

Local Closed-World Reasoning With Description Logics Under The Well-Founded Semantics, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler

Computer Science and Engineering Faculty Publications

An important question for the upcoming Semantic Web is how to best combine open world ontology languages, such as the OWL-based ones, with closed world rule-based languages. One of the most mature proposals for this combination is known as hybrid MKNF knowledge bases (Motik and Rosati, 2010 [52]), and it is based on an adaptation of the Stable Model Semantics to knowledge bases consisting of ontology axioms and rules. In this paper we propose a well-founded semantics for nondisjunctive hybrid MKNF knowledge bases that promises to provide better efficiency of reasoning, and that is compatible with both the OWL-based …

Automatic Domain Model Creation Using Pattern-Based Fact Extraction, Christopher Thomas, Pankaj Mehra, Wenbo Wang, Amit P. Sheth, Gerhard Weikum, Victor Chan

Kno.e.sis Publications

This paper describes a minimally guided approach to automatic domain model creation. The first step is to carve an area of interest out of the Wikipedia hierarchy based on a simple query or other starting point. The second step is to connect the concepts in this domain hierarchy with named relationships. A starting point is provided by Linked Open Data, such as DBPedia. Based on these community-generated facts we train a pattern-based fact-extraction algorithm to augment a domain hierarchy with previously unknown relationship occurrences. Pattern vectors are learned that represent occurrences of relationships between concepts. The process described can be …

Privacy-By-Design In Federated Social Web Applications, Alexandre Passant, Owen Sacco, Julia Anaya, Pavan Kapanipathi

Kno.e.sis Publications

No abstract provided.

Topical Keyphrase Extraction From Twitter, Xin Zhao, Jing Jiang, Jing He, Yang Song, Palakorn Achananuparp, Ee Peng Lim, Xiaoming Li

Research Collection School Of Computing and Information Systems

Summarizing and analyzing Twitter content is an important and challenging task. In this paper, we propose to extract topical keyphrases as one way to summarize Twitter. We propose a context-sensitive topical PageRank method for keyword ranking and a probabilistic scoring function that considers both relevance and interestingness of keyphrases for keyphrase ranking. We evaluate our proposed methods on a large Twitter data set. Experiments show that these methods are very effective for topical keyphrase extraction.

Getting To Know Social Media Analytics, Tin Seong Kam

Research Collection School Of Computing and Information Systems

Over the last five years, the unprecedented development and use of social mediating technologies such as blog, wiki, Facebook, and Tweeter have engendered radically new ways of working, playing, and creating meaning, leaving an indelible mark on nearly every domain imaginable. Despite the growing ubiquity of social mediating technologies, their potential has hardly been tapped. Effectively using data collected from social mediating technologies by the business community is far from trivial. This is mainly due to the general lack of awareness on Social Network Analysis (SNA) techniques and technologies among the business analysts and practitioners. This presentation aims to provide …