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Full-Text Articles in Social and Behavioral Sciences

Gender-Based Violence In 140 Characters Or Fewer: A #Bigdata Case Study Of Twitter, Hemant Purohit, Tanvi Banerjee, Andrew Hampton, Valerie L. Shalin, Nayanesh Bhandutia, Amit P. Sheth Jul 2015

Gender-Based Violence In 140 Characters Or Fewer: A #Bigdata Case Study Of Twitter, Hemant Purohit, Tanvi Banerjee, Andrew Hampton, Valerie L. Shalin, Nayanesh Bhandutia, Amit P. Sheth

Amit P. Sheth

Public institutions are increasingly reliant on data from social media sites to measure public attitude and provide timely public engagement. Such reliance includes the exploration of public views on important social issues such as gender-based violence (GBV). In this study, we examine big (social) data consisting of nearly fourteen million tweets collected from Twitter over a period of ten months to analyze public opinion regarding GBV, highlighting the nature of tweeting practices by geographical location and gender. We demonstrate the utility of Computational Social Science to mine insight from the corpus while accounting for the influence of both transient events ...


Entity Recommendations Using Hierarchical Knowledge Bases, Siva Kumar Cheekula, Pavan Kapanipathi, Derek Doran, Prateek Jain, Amit P. Sheth Jul 2015

Entity Recommendations Using Hierarchical Knowledge Bases, Siva Kumar Cheekula, Pavan Kapanipathi, Derek Doran, Prateek Jain, Amit P. Sheth

Amit P. Sheth

Recent developments in recommendation algorithms have focused on integrating Linked Open Data to augment traditional algorithms with background knowledge. These developments recognize that the integration of Linked Open Data may or better performance, particularly in cold start cases. In this paper, we explore if and how a specific type of Linked Open Data, namely hierarchical knowledge, may be utilized for recommendation systems. We propose a content-based recommendation approaches that adapts a spreading activation algorithm over the DBpedia category structure to identify entities of interest to the user. Evaluation of the algorithm over the Movielens dataset demonstrates that our method yields ...


"Time For Dabs": Analyzing Twitter Data On Butane Hash Oil Use, Raminta Daniulaityte, Robert G. Carlson, Farahnaz Golroo, Sanjaya Wijeratne, Edward W. Boyer, Silvia S. Martins, Ramzi W. Nahhas, Amit P. Sheth Jul 2015

"Time For Dabs": Analyzing Twitter Data On Butane Hash Oil Use, Raminta Daniulaityte, Robert G. Carlson, Farahnaz Golroo, Sanjaya Wijeratne, Edward W. Boyer, Silvia S. Martins, Ramzi W. Nahhas, Amit P. Sheth

Amit P. Sheth

No abstract provided.


Analyzing The Social Media Footprint Of Street Gangs, Sanjaya Wijeratne, Derek Doran, Amit P. Sheth, Jack Dustin Jul 2015

Analyzing The Social Media Footprint Of Street Gangs, Sanjaya Wijeratne, Derek Doran, Amit P. Sheth, Jack Dustin

Amit P. Sheth

Gangs utilize social media as a way to maintain threatening virtual presences, to communicate about their activities, and to intimidate others. Such usage has gained the attention of many justice service agencies that wish to create better crime prevention and judicial services. However, these agencies use analysis methods that are labor intensive and only lead to basic, qualitative data interpretations. This paper presents the architecture of a modern platform to discover the structure, function, and operation of gangs through the lens of social media. Preliminary analysis of social media posts shared in the greater Chicago, IL region demonstrate the platform ...


Smart Data - How You And I Will Exploit Big Data For Personalized Digital Health And Many Other Activities, Amit P. Sheth Jul 2015

Smart Data - How You And I Will Exploit Big Data For Personalized Digital Health And Many Other Activities, Amit P. Sheth

Amit P. Sheth

No abstract provided.


Big Data And Smart Cities, Amit P. Sheth Jul 2015

Big Data And Smart Cities, Amit P. Sheth

Amit P. Sheth

No abstract provided.


Knowledge Enabled Approach To Predict The Location Of Twitter Users, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan Jul 2015

Knowledge Enabled Approach To Predict The Location Of Twitter Users, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan

Amit P. Sheth

Knowledge bases have been used to improve performance in applications ranging from web search and event detection to entity recognition and disambiguation. More recently, knowledge bases have been used to analyze social data. A key challenge in social data analysis has been the identification of the geographic location of online users in a social network such as Twitter. Existing approaches to predict the location of users, based on their tweets, rely solely on social media features or probabilistic language models. These approaches are supervised and require large training dataset of geo-tagged tweets to build their models. As most Twitter users ...


Knowledge-Driven Personalized Contextual Mhealth Service For Asthma Management In Children, Pramod Anantharam, Tanvi Banerjee, Amit P. Sheth, Krishnaprasad Thirunarayan, Surendra Marupudi, Vaikunth Sridharan Jul 2015

Knowledge-Driven Personalized Contextual Mhealth Service For Asthma Management In Children, Pramod Anantharam, Tanvi Banerjee, Amit P. Sheth, Krishnaprasad Thirunarayan, Surendra Marupudi, Vaikunth Sridharan

Amit P. Sheth

Wide adoption of smartphones and availability of low-cost sensors has resulted in seamless and continuous monitoring of physiology, environment, and public health notifications. However, personalized digital health and patient empowerment can become a reality only if the complex multisensory and multimodal data is processed within the patient context. Contextual processing of patient data along with personalized medical knowledge can lead to actionable information for better and timely decisions. We present a system called kHealth capable of aggregating multisensory and multimodal data from sensors (passive sensing) and answers to questionnaire (active sensing) from patients with asthma. We present our preliminary data ...


Semantic Gateway As A Service Architecture For Iot Interoperability, Pratikkumar Desai, Amit P. Sheth, Pramod Anantharam Jul 2015

Semantic Gateway As A Service Architecture For Iot Interoperability, Pratikkumar Desai, Amit P. Sheth, Pramod Anantharam

Amit P. Sheth

The Internet of Things (IoT) is set to occupy a substantial component of future Internet. The IoT connects sensors and devices that record physical observations to applications and services of the Internet. As a successor to technologies such as RFID and Wireless Sensor Networks (WSN), the IoT has stumbled into vertical silos of proprietary systems, providing little or no interoperability with similar systems. As the IoT represents future state of the Internet, an intelligent and scalable architecture is required to provide connectivity between these silos, enabling discovery of physical sensors and interpretation of messages between things. This paper proposes a ...


Some Trust Issues In Social Networks And Sensor Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth Dec 2014

Some Trust Issues In Social Networks And Sensor Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth

Amit P. Sheth

Trust and reputation are becoming increasingly important in diverse areas such as search, e-commerce, social media, semantic sensor networks, etc. We review past work and explore future research issues relevant to trust in social/sensor networks and interactions. We advocate a balanced, iterative approach to trust that marries both theory and practice. On the theoretical side, we investigate models of trust to analyze and specify the nature of trust and trust computation. On the practical side, we propose to uncover aspects that provide a basis for trust formation and techniques to extract trust information from concrete social/sensor networks and ...


Iexplore: Interactive Browsing And Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Jagannathan Srinivasan, Todd Minning, Thomas Rindflesch, Bastien Rance, Ramakanth Kavuluru, Himi Yalamanchili, Krishnaprasad Thirunarayan, Satya S. Sahoo, Amit P. Sheth Dec 2014

Iexplore: Interactive Browsing And Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Jagannathan Srinivasan, Todd Minning, Thomas Rindflesch, Bastien Rance, Ramakanth Kavuluru, Himi Yalamanchili, Krishnaprasad Thirunarayan, Satya S. Sahoo, Amit P. Sheth

Amit P. Sheth

We present iExplore, a Semantic Web based application that helps biomedical researchers study and explore biomedical knowledge interactively. iExplore uses the Biomedical Knowledge Repository (BKR), which integrates knowledge from various sources ranging from information extracted from biomedical literature (from PubMed) to many structured vocabularies in the Unified Medical Language System (UMLS). The current version of BKR provides a unified provenance representation for 12 million semantic predications (triples with a predicate connecting a subject and an object) derived from 87 vocabulary families in the UMLS and 14 million predications extracted from 21 million PubMed abstracts. To engage the domain experts in ...


Semantics And Services Enabled Problem Solving Environment For Trypanosoma Cruzi, Amit P. Sheth, Rick L. Tarleton, Mark Musen, Satya S. Sahoo, Prashant Doshi, Natasha Noy Dec 2014

Semantics And Services Enabled Problem Solving Environment For Trypanosoma Cruzi, Amit P. Sheth, Rick L. Tarleton, Mark Musen, Satya S. Sahoo, Prashant Doshi, Natasha Noy

Amit P. Sheth

No abstract provided.


Faces: Diversity-Aware Entity Summarization Using Incremental Hierarchical Conceptual Clustering, Kalpa Gunaratna, Krishnaprasad Thirunarayan, Amit P. Sheth Dec 2014

Faces: Diversity-Aware Entity Summarization Using Incremental Hierarchical Conceptual Clustering, Kalpa Gunaratna, Krishnaprasad Thirunarayan, Amit P. Sheth

Amit P. Sheth

Semantic Web documents that encode facts about entities on the Web have been growing rapidly in size and evolving over time. Creating summaries on lengthy Semantic Web documents for quick identification of the corresponding entity has been of great contemporary interest. In this paper, we explore automatic summarization techniques that characterize and enable identification of an entity and create summaries that are human friendly. Specifically, we highlight the importance of diversified (faceted) summaries by combining three dimensions: diversity, uniqueness, and popularity. Our novel diversity-aware entity summarization approach mimics human conceptual clustering techniques to group facts, and picks representative facts from ...


Extracting City Traffic Events From Social Streams, Pramod Anantharam, Payam Barnaghi, Krishnaprasad Thirunarayan, Amit P. Sheth Dec 2014

Extracting City Traffic Events From Social Streams, Pramod Anantharam, Payam Barnaghi, Krishnaprasad Thirunarayan, Amit P. Sheth

Amit P. Sheth

Cities are composed of complex systems with physical, cyber, and social components. Current works on extracting and understanding city events mainly rely on technology enabled infrastructure to observe and record events. In this work, we propose an approach to leverage citizen observations of various city systems and services such as traffic, public transport, water supply, weather, sewage, and public safety as a source of city events. We investigate the feasibility of using such textual streams for extracting city events from annotated text. We formalize the problem of annotating social streams such as microblogs as a sequence labeling problem. We present ...


Semantic (Web) Technology In Action: Ontology Driven Information Systems For Search, Integration, And Analysis, Amit P. Sheth, Cartic Ramakrishnan Dec 2014

Semantic (Web) Technology In Action: Ontology Driven Information Systems For Search, Integration, And Analysis, Amit P. Sheth, Cartic Ramakrishnan

Amit P. Sheth

Semantics is seen as the key ingredient in the next phase of the Web infrastructure as well as the next generation of information systems applications. In this context, we review some of the reservations expressed about the viability of the Semantic Web. We respond to these by identifying a Semantic Technology that supports the key capabilities also needed to realize the Semantic Web vision, namely representing, acquiring and utilizing knowledge. Given that scalability is a key challenge, we briefly review our observations from developing three classes of real world applications and corresponding technology components: search/browsing, integration, and analytics. We ...


Automatic Domain Model Creation Using Pattern-Based Fact Extraction, Christopher Thomas, Pankaj Mehra, Wenbo Wang, Amit P. Sheth, Gerhard Weikum, Victor Chan Dec 2014

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

Amit P. Sheth

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 ...


Location Prediction Of Twitter Users Using Wikipedia, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan Dec 2014

Location Prediction Of Twitter Users Using Wikipedia, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan

Amit P. Sheth

The mining of user generated content in social media has proven very effective in domains ranging from personalization and recommendation systems to crisis management. The knowledge of online users locations makes their tweets more informative and adds another dimension to their analysis. Existing approaches to predict the location of Twitter users are purely data-driven and require large training data sets of geo-tagged tweets. The collection and modelling process of tweets can be time intensive. To overcome this drawback, we propose a novel knowledge based approach that does not require any training data. Our approach uses information in Wikipedia, about cities ...


Ontology Supported Knowledge Discovery In The Field Of Human Performance And Cognition, Christopher Thomas, Pablo N. Mendes, Delroy H. Cameron, Amit P. Sheth, Krishnaprasad Thirunarayan, Cartic Ramakrishnan Dec 2014

Ontology Supported Knowledge Discovery In The Field Of Human Performance And Cognition, Christopher Thomas, Pablo N. Mendes, Delroy H. Cameron, Amit P. Sheth, Krishnaprasad Thirunarayan, Cartic Ramakrishnan

Amit P. Sheth

No abstract provided.


Semantics-Empowered Big Data Processing With Applications, Krishnaprasad Thirunarayan, Amit P. Sheth Dec 2014

Semantics-Empowered Big Data Processing With Applications, Krishnaprasad Thirunarayan, Amit P. Sheth

Amit P. Sheth

We discuss the nature of Big Data and address the role of semantics in analyzing and processing Big Data that arises in the context of Physical-Cyber-Social Systems. We organize our research around the Five Vs of Big Data, where four of the Vs are harnessed to produce the fifth V - value. To handle the challenge of Volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision-making. To handle the challenge of Variety, we resort to the use of semantic models and annotations of data so that much of the intelligent processing can ...


Ranking Complex Relationships On The Semantic Web, Boanerges Aleman-Meza, Christian Halaschek-Wiener, I. Budak Arpinar, Cartic Ramakrishnan, Amit P. Sheth Oct 2014

Ranking Complex Relationships On The Semantic Web, Boanerges Aleman-Meza, Christian Halaschek-Wiener, I. Budak Arpinar, Cartic Ramakrishnan, Amit P. Sheth

Amit P. Sheth

Industry and academia are both focusing their attention on information retrieval over semantic metadata extracted from the Web, and it is increasingly possible to analyze such metadata to discover interesting relationships. However, just as document ranking is a critical component in today's search engines, the ranking of complex relationships would be an important component in tomorrow's semantic Web engines. This article presents a flexible ranking approach to identify interesting and relevant relationships in the semantic Web. The authors demonstrate the scheme's effectiveness through an empirical evaluation over a real-world data set.


Realizing The Relationship Web: Morphing Information Access On The Web From Today's Document- And Entity-Centric Paradigm To A Relationship-Centric Paradigm, Amit P. Sheth Oct 2014

Realizing The Relationship Web: Morphing Information Access On The Web From Today's Document- And Entity-Centric Paradigm To A Relationship-Centric Paradigm, Amit P. Sheth

Amit P. Sheth

No abstract provided.


Lifecycle Of Semantic Web Processes, Jorge Cardoso, Chistoph Bussler, Amit P. Sheth Oct 2014

Lifecycle Of Semantic Web Processes, Jorge Cardoso, Chistoph Bussler, Amit P. Sheth

Amit P. Sheth

This tutorial presents what can be achieved by symbiotic synthesis of two of the most important research and technology application areas: Web Services and the Semantic Web. It presents the more recent evolution of the Web Service platform towards rich Web Service and process model annotation, and explores some of the promises and challenges in applying semantics to each of the steps in the Semantic Web Process lifecycle.


The 4 X 4 Semantic Model: Exploiting Data, Functional, Non-Functional And Execution Semantics Across Business Process, Workflow, Partner Services And Middleware Services Tiers, Amit P. Sheth, Karthik Gomadam Oct 2014

The 4 X 4 Semantic Model: Exploiting Data, Functional, Non-Functional And Execution Semantics Across Business Process, Workflow, Partner Services And Middleware Services Tiers, Amit P. Sheth, Karthik Gomadam

Amit P. Sheth

Business processes in the global environment increasingly encompass multiple partners and complex, rapidly changing requirements. In this context it is critical that strategic business objectives align with and map accurately to systems that support flexible and dynamic business processes. To support the demanding requirements of global business processes, we propose a comprehensive, unifying 4 X 4 Semantic Model that uses Semantic Templates to link four tiers of implementation with four types of semantics. The four tiers are the Business Process Tier, the Workflow Enactment Tier, the Partner Services Tier, and the Middleware Services Tier. The four types of semantics are ...


Enhancing Web Services Description And Discovery To Facilitate Composition, Preeda Rajasekaran, John A. Miller, Kunal Verma, Amit P. Sheth Oct 2014

Enhancing Web Services Description And Discovery To Facilitate Composition, Preeda Rajasekaran, John A. Miller, Kunal Verma, Amit P. Sheth

Amit P. Sheth

Web services are in the midst of making the transition from being a promising technology to being widely used in the industry. However, most efforts to use Web services have been manual, thus slowing down the ever changing and dynamic businesses of today. In this paper, we contend that more expressive descriptions of Web services will lead to greater automation and thus provide more agility to businesses. We present the METEOR-S front-end tools for source code annotation and semantic Web service description generation. We also present WSDL-S, a language created for incorporating semantic descriptions in the industry wide accepted WSDL ...


A Local Qualitative Approach To Referral And Functional Trust, Krishnaprasad Thirunarayan, Dharan Althuru, Cory Andrew Henson, Amit P. Sheth Oct 2014

A Local Qualitative Approach To Referral And Functional Trust, Krishnaprasad Thirunarayan, Dharan Althuru, Cory Andrew Henson, Amit P. Sheth

Amit P. Sheth

Trust and confidence are becoming key issues in diverse applications such as ecommerce, social networks, semantic sensor web, semantic web information retrieval systems, etc. Both humans and machines use some form of trust to make informed and reliable decisions before acting. In this work, we briefly review existing work on trust networks, pointing out some of its drawbacks. We then propose a local framework to explore two different kinds of trust among agents called referral trust and functional trust, that are modelled using local partial orders, to enable qualitative trust personalization. The proposed approach formalizes reasoning with trust, distinguishing between ...


Are Twitter Users Equal In Predicting Elections? A Study Of User Groups In Predicting 2012 U.S. Republican Primaries, Lu Chen, Wenbo Wang, Amit P. Sheth Oct 2014

Are Twitter Users Equal In Predicting Elections? A Study Of User Groups In Predicting 2012 U.S. Republican Primaries, Lu Chen, Wenbo Wang, Amit P. Sheth

Amit P. Sheth

Existing studies on predicting election results are under the assumption that all the users should be treated equally. However, recent work [14] shows that social media users from different groups (e.g., “silent majority” vs. “vocal minority”) have significant differences in the generated content and tweeting behavior. The effect of these differences on predicting election results has not been exploited yet. In this paper, we study the spectrum of Twitter users who participate in the on-line discussion of 2012 U.S. Republican Presidential Primaries, and examine the predictive power of different user groups (e.g., highly engaged users vs. lowly ...


An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak Oct 2014

An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak

Amit P. Sheth

Increasingly, individuals are taking active participation in learning and managing their health by leveraging online resources. Understanding online health information searching behavior can help us to study what health topics users search for and how search queries are formulated. In this work, we analyzed 10 million cardiovascular diseases (CVD) related search queries from MayoClinic.com. We performed semantic analysis on the queries using UMLS MetaMap and analyzed structural and textual properties as well as linguistic characteristics of the queries.


Why Gujarat Needs Much Better Higher Education & Research To Succeed In Knowledge Economy & What We Can Do About It?, Amit P. Sheth, Kamlesh Lulla, Sanjay Chaudhary Oct 2014

Why Gujarat Needs Much Better Higher Education & Research To Succeed In Knowledge Economy & What We Can Do About It?, Amit P. Sheth, Kamlesh Lulla, Sanjay Chaudhary

Amit P. Sheth

This white paper distills the deliberations on the role of higher education and research as a key enabler of a Knowledge based Society. In particular it discusses (a) the importance of higher quality PhDs for building a knowledge society, (b) the initiatives and progress in competing economies in higher education and research, (c) where Gujarat stands in comparison, and (d) some recommendations on what Gujarat can do to enable timely progress towards building a knowledge based society and economy. These deliberations were conducted in conjunction with the International Conference on 'Reconnecting Gujarati Diaspora with its Homeland: Contribution to its Development ...


Context And Domain Knowledge Enhanced Entity Spotting In Informal Text, Daniel Gruhl, Meena Nagarajan, Jan Pieper, Christine Robson, Amit P. Sheth Oct 2014

Context And Domain Knowledge Enhanced Entity Spotting In Informal Text, Daniel Gruhl, Meena Nagarajan, Jan Pieper, Christine Robson, Amit P. Sheth

Amit P. Sheth

This paper explores the application of restricted relationship graphs (RDF) and statistical NLP techniques to improve named entity annotation in challenging Informal English domains. We validate our approach using on-line forums discussing popular music. Named entity annotation is particularly difficult in this domain because it is characterized by a large number of ambiguous entities, such as the Madonna album “Music” or Lilly Allen’s pop hit “Smile”.

We evaluate improvements in annotation accuracy that can be obtained by restricting the set of possible entities using real-world constraints. We find that constrained domain entity extraction raises the annotation accuracy significantly, making ...


Discovering Fine-Grained Sentiment In Suicide Notes, Wenbo Wang, Lu Chen, Ming Tan, Shaojun Wang, Amit P. Sheth Oct 2014

Discovering Fine-Grained Sentiment In Suicide Notes, Wenbo Wang, Lu Chen, Ming Tan, Shaojun Wang, Amit P. Sheth

Amit P. Sheth

This paper presents our solution for the i2b2 sentiment classification challenge. Our hybrid system consists of machine learning and rule-based classifiers. For the machine learning classifier, we investigate a variety of lexical, syntactic and knowledge-based features, and show how much these features contribute to the performance of the classifier through experiments. For the rule-based classifier, we propose an algorithm to automatically extract effective syntactic and lexical patterns from training examples. The experimental results show that the rule-based classifier outperforms the baseline machine learning classifier using unigram features. By combining the machine learning classifier and the rule-based classifier, the hybrid system ...