OS and Networks Commons^™

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 …

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: - …

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.

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.

Trust Networks: Interpersonal, Social, And Sensor, Krishnaprasad Thirunarayan, Pramod Anantharam

Kno.e.sis Publications

Trust relationships occur naturally in many diverse contexts such as ecommerce, interpersonal interactions, social networks, sensor web, etc. As agents providing content and services become increasingly removed from the agents that consume them, the issue of robust trust inference and update become critical. Unfortunately, there is neither a universal notion of trust that is applicable to all domains nor a clear explication of its semantics or computation in many situations. In this beginner's level tutorial, we motivate the trust problem, explain the relevant concepts, summarize research in modeling trust and gleaning trustworthiness, and discuss challenges confronting us in this process.

Identifying And Implementing The Underlying Operators For Nuclear Magnetic Resonance Based Metabolomics Data Analysis, Ashwin Manjunatha, Ajith H. Ranabahu, Paul E. Anderson, Amit P. Sheth

Kno.e.sis Publications

The science of metabolomics is a relatively young field that requires intensive signal processing and multivariate data analysis for interpretation of experimental results. The lack of integration and standardization for metabolomics compounded by the complexity of the experimental data has lead to a fragmented research community. While efforts have been undertaken to approach these problems, the efforts to develop a set of standards for reporting processing and analysis procedures has stalled.

In this paper, we propose a set of fundamental operators for nuclear magnetic resonance(NMR) based metabolomics. These operators are implementation independent, and can be used to easily and precisely …

A Genetic Optimization Approach For Isolating Translational Efficiency Bias, Douglas W. Raiford, Dan E. Krane, Travis E. Doom, Michael L. Raymer

Kno.e.sis Publications

The study of codon usage bias is an important research area that contributes to our understanding of molecular evolution, phylogenetic relationships, respiratory lifestyle, and other characteristics. Translational efficiency bias is perhaps the most well studied codon usage bias, as it is frequently utilized to predict relative protein expression levels. We present a novel approach to isolating translational efficiency bias in microbial genomes. There are several existent methods for isolating translational efficiency bias. Previous approaches are susceptible to the confounding influences of other potentially dominant biases. Additionally, existing approaches to identifying translational efficiency bias generally require both genomic sequence information and …

A Systematic Property Mapping Using Category Hierarchy And Data, Kalpa Gunaratna, Sarasi Lalithsena, Prateek Jain, Cory Andrew Henson, Amit P. Sheth

Kno.e.sis Publications

Relationships play a key role in Semantic Web to connect the dots between entities (concepts or instances in a way that enables to absorb the real sense of the entities. Even though relationships are important, it is difficult to categorize or identify them because they consist of complex knowledge in the schema. Therefore systematically identifying relationships yield many advantages and open doors for new research avenues. In this work, we try to identify a specific type of relationship (part of) in a multi-domain dataset and devised an algorithm using Wikipedia to identify patterns of part of relationships in the dataset. …

Cloudvista: Visual Cluster Exploration For Extreme Scale Data In The Could, Keke Chen, Huiqi Xi, Fengguang Tian, Shumin Guo

Kno.e.sis Publications

The problem of efficient and high-quality clustering of extreme scale datasets with complex clustering structures continues to be one of the most challenging data analysis problems. An innovate use of data cloud would provide unique opportunity to address this challenge. In this paper, we propose the CloudVista framework to address (1) the problems caused by using sampling in the existing approaches and (2) the problems with the latency caused by cloud-side processing on interactive cluster visualization. The CloudVista framework aims to explore the entire large data stored in the cloud with the help of the data structure visual frame and …

Analysis On Partial Relationship In Lod, Kalpa Gunaratna, Sarasi Lalithsena, Cory Andrew Henson, Prateek Jain

Kno.e.sis Publications

Relationships play a key role in Semantic Web to connect the dots between entities (concepts or instances) in a way that enables to absorb the real sense of the entities. Some interesting relationships would give proof for the existence of subject and object in triples which in tern can be defined as evidential relationships. Identifying evidential relationships will yield solutions to some existing inference problems and open doors for new applications and research. Part_of relationships are identified as a special kind of an evidential relationship out of membership, causality and etc. Linked Open data as a global data space would …

Contextual Ontology Alignment Of Lod With An Upper Ontology: A Case Study With Proton, Prateek Jain, Peter Z. Yeh, Kunal Verma, Reymonrod G. Vasquez, Mariana Darnorva, Pascal Hitzler, Amit P. Sheth

Kno.e.sis Publications

The Linked Open Data (LOD) is a major milestone towards realizing the Semantic Web vision, and can enable applications such as robust Question Answering (QA) systems that can answer queries requiring multiple, disparate information sources. However, realizing these applications requires relationships at both the schema and instance level, but currently the LOD only provides relationships for the latter. To address this limitation, we present a solution for automatically finding schema-level links between two LOD ontologies – in the sense of ontology alignment. Our solution, called BLOOMS+, extends our previous solution (i.e. BLOOMS) in two significant ways. BLOOMS+ 1) uses a …

Privacy-Aware An Scalable Content Dissemination In Distributed Social Networks, Pavan Kapanipathi, Julia Anaya, Amit P. Sheth, Brett Slatkin, Alexandre Passant

Kno.e.sis Publications

Centralized social networking websites raise scalability issues - due to the growing number of participants - and, as well as, policy concerns - such as control, privacy and ownership over the user's published data. Distributed Social Networks aim to solve this issue by enabling architecture where people own their data and share it their own way. However, the privacy and scalability challenge is still to be tackled. This paper presents a privacy-aware extension to Google's PubSubHubbub protocol, using Semantic Web technologies, solving both the scalability and the privacy issues in Distributed Social Networks. We enhanced the traditional feature of PubSubHubbub …

Semantic Social Mashup Approach For Designing Citizen Diplomacy, Amit P. Sheth

Kno.e.sis Publications

Advancement in technology has brought exceptional connectivity, easy and open access to communication mediums via Internet. Everyday millions of people are interactively communicating to each other and sharing multimedia content through Social Media/Networks, Web-based and mobile-based technologies. Social media provides variety of interesting, engaging applications such as Twitter, Facebook, YouTube, Flicker, Blogs. People interested in contributing to global welfare and improving humanity are connected to various NGO's like Red Cross, Ushahidi (www.ushahidi.com), eMoksha (emoksha.org), etc. Social media and NGOs are acting as an excellent medium of communication and sharing, connected diverse people irrespective of their nationality, religion, culture, etc. Social …

Citizen Sensor Data Mining, Social Media Analytics And Development Centric Web Applications, Meenakshi Nagarajan, Amit P. Sheth, Selvam Velmuru

Kno.e.sis Publications

With the rapid rise in the popularity of social media (500M+ Facebook users, 100M+ twitter users), and near ubiquitous mobile access (4.1 billion actively-used mobile phones), the sharing of observations and opinions has become common-place (nearly 100M tweets a day, 1.8 trillion SMSs in US last year). This has given us an unprecedented access to the pulse of a populace and the ability to perform analytics on social data to support a variety of socially intelligent applications -- be it towards targeted online content delivery, crisis management, organizing revolutions or promoting social development in underdeveloped and developing countries. This tutorial …

A Unified Framework Fro Managing Provenance Information In Translational Research, Satya S. Sahoo, Vinh Nguyen, Olivier Bodenreider, Priti Parikh, Todd Minning, Amit P. Sheth

Kno.e.sis Publications

Background

A critical aspect of the NIH Translational Research roadmap, which seeks to accelerate the delivery of "bench-side" discoveries to patient's "bedside," is the management of the provenance metadata that keeps track of the origin and history of data resources as they traverse the path from the bench to the bedside and back. A comprehensive provenance framework is essential for researchers to verify the quality of data, reproduce scientific results published in peer-reviewed literature, validate scientific process, and associate trust value with data and results. Traditional approaches to provenance management have focused on only partial sections of the translational research …

The Cloud Agnostic E-Science Analysis Platform, Ajith Harshana Ranabahu, Paul E. Anderson, Amit P. Sheth

Kno.e.sis Publications

The amount of data being generated for e-Science domains has grown exponentially in the past decade, yet the adoption of new computational techniques in these fields hasn't seen similar improvements. The presented platform can exploit the power of cloud computing while providing abstractions for scientists to create highly scalable data processing workflows.

Demonstration: Real-Time Semantic Analysis Of Sensor Streams, Harshal Kamlesh 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. With this coming data explosion, real-time analytics software must either adapt or die. 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 into feature …

Spatial Semantics For Better Interoperability And Analysis: Challenges And Experiences In Building Semantically Rich Applications In Web 3.0, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Flexible Bootstrapping-Based Ontology Alignment, Prateek Jain, Pascal Hitzler, Amit P. Sheth

Kno.e.sis Publications

BLOOMS (Jain et al, ISWC2010) is an ontology alignment system which, in its core, utilizes the Wikipedia category hierarchy for establishing alignments. In this paper, we present a Plug-and-Play extension to BLOOMS, which allows to flexibly replace or complement the use of Wikipedia by other online or offline resources, including domain-specific ontologies or taxonomies. By making use of automated translation services and of Wikipedia in languages other than English, it makes it possible to apply BLOOMS to alignment tasks where the input ontologies are written in different languages.

Ontology Alignment For Linked Open Data, Prateek Jain, Pascal Hitzler, Amit P. Sheth, Kunal Verma, Peter Z. Yeh

Kno.e.sis Publications

The Web of Data currently coming into existence through the Linked Open Data (LOD) effort is a major milestone in realizing the Semantic Web vision. However, the development of applications based on LOD faces difficulties due to the fact that the different LOD datasets are rather loosely connected pieces of information. In particular, links between LOD datasets are almost exclusively on the level of instances, and schema-level information is being ignored. In this paper, we therefore present a system for finding schema-level links between LOD datasets in the sense of ontology alignment. Our system, called BLOOMS, is based on the …

A Taxonomy-Based Model For Expertise Extrapolation, Delroy H. Cameron, Boanerges Aleman-Meza, Ismailcem Budak Arpinar, Sheron L. Decker, Amit P. Sheth

Kno.e.sis Publications

While many ExpertFinder applications succeed in finding experts, their techniques are not always designed to capture the various levels at which expertise can be expressed. Indeed, expertise can be inferred from relationships between topics and subtopics in a taxonomy. The conventional wisdom is that expertise in subtopics is also indicative of expertise in higher level topics as well. The enrichment of Expertise Profiles for finding experts can therefore be facilitated by taking domain hierarchies into account. We present a novel semantics-based model for finding experts, expertise levels and collaboration levels in a peer review context, such as composing a Program …

Ranking Documents Semantically Using Ontological Relationships, Boanerges Aleman-Meza, I. Budak Arpinar, Mustafa V. Nural, Amit P. Sheth

Kno.e.sis Publications

Although arguable success of today’s keyword based search engines in certain information retrieval tasks, ranking search results in a meaningful way remains an open problem. In this work, the goal is to use of semantic relationships for ranking documents without relying on the existence of any specific structure in a document or links between documents. Instead, real-world entities are identified and the relevance of documents is determined using relationships that are known to exist between the entities in a populated ontology. We introduce a measure of relevance that is based on traversal and the semantics of relationships that link entities …

Pattern Space Maintenance For Data Updates And Interactive Mining, Mengling Feng, Guozhu Dong, Jinyan Li, Yap-Peng Tan, Limsoon Wong

Kno.e.sis Publications

This article addresses the incremental and decremental maintenance of the frequent pattern space. We conduct an in-depth investigation on how the frequent pattern space evolves under both incremental and decremental updates. Based on the evolution analysis, a new data structure, Generator-Enumeration Tree (GE-tree), is developed to facilitate the maintenance of the frequent pattern space. With the concept of GE-tree, we propose two novel algorithms, Pattern Space Maintainer+ (PSM+) and Pattern Space Maintainer− (PSM−), for the incremental and decremental maintenance of frequent patterns. Experimental results demonstrate that the proposed algorithms, on average, outperform the representative state-of-the-art …

Cross-Market Model Adaptation With Pairwise Preference Data For Web Search Ranking, Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, Keke Chen

Kno.e.sis Publications

Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibility required of a commercial web search. However, manually labeled training data (with multiple absolute grades) has become the bottleneck for training a quality ranking function, particularly for a new domain. In this paper, we explore the adaptation of machine-learned ranking models across a set of geographically diverse markets with the market-specific pairwise preference data, which can be easily obtained from clickthrough logs. We propose a novel adaptation algorithm, Pairwise-Trada, which is able to adapt ranking models that are trained …

Trust Model For Semantic Sensor And Social Networks: A Preliminary Report, Pramod Anantharam, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Trust is an amorphous concept that is becoming Increasingly important in many domains, such as P2P networks, E-commerce, social networks, and sensor networks. While we all have an intuitive notion of trust, the literature is scattered with a wide assortment of differing definitions and descriptions; often these descriptions are highly dependent on a single domain or application of interest. In addition, they often discuss orthogonal aspects of trust while continuing to use the general term “trust”. In order to make sense of the situation, we have developed an ontology of trust that integrates and relates its various aspects into a …

Sit-To-Stand Detection Using Fuzzy Clustering Techniques, Tanvi Banerjee, James M. Keller, Marjorie Skubic, Carmen Abbott

Kno.e.sis Publications

The ability to rise from a chair is an important parameter to assess the balance deficits of a person. In particular, this can be an indication of risk for falling in elderly persons. Our goal is automated assessment of fall risk using video data. Towards this goal, we present a simple yet effective method of detecting transition, i.e. sit-to-stand and stand-to-sit, from image frames using fuzzy clustering methods on image moments. The technique described in this paper is shown to be robust even in the presence of noise and has been tested on several data sequences using different subjects yielding …