Computer Sciences Commons^™

Domain-Specific Document Retrieval Framework For Near Real-Time Social Health Data, Swapnil Soni

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With the advent of web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these services to share and seek health information in real-time has increased exponentially. Recently, Twitter has emerged as one of the primary mediums for sharing and seeking of the latest information related to a variety of topics, including health information. Although Twitter is an excellent information source, the identification of useful information from the deluge of tweets is one of the major challenges. Twitter search is limited to keyword-based techniques to retrieve information for a given query and sometimes the results do not …

Automatic Emotion Identification From Text, Wenbo Wang

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People's emotions can be gleaned from their text using machine learning techniques to build models that exploit large self-labeled emotion data from social media. Further, the self-labeled emotion data can be effectively adapted to train emotion classifiers in different target domains where training data are sparse.

Emotions are both prevalent in and essential to most aspects of our lives. They influence our decision-making, affect our social relationships and shape our daily behavior. With the rapid growth of emotion-rich textual content, such as microblog posts, blog posts, and forum discussions, there is a growing need to develop algorithms and techniques for …

Knowledge Enabled Location Prediction Of Twitter Users, Revathy Krishnamurthy

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As the popularity of online social networking sites such as Twitter and Facebook continues to rise, the volume of textual content generated on the web is increasing rapidly. The mining of user generated content in social media has proven effective in domains ranging from personalization and recommendation systems to crisis management. These applications stand to be further enhanced by incorporating information about the geo-position of social media users in their analysis. Due to privacy concerns, users are largely reluctant to share their location information. As a consequence of this, researchers have focused on automatic inferencing of location information from the …

A Language For Inconsistency-Tolerant Ontology Mapping, Kunal Sengupta

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Ontology alignment plays a key role in enabling interoperability among various data sources present in the web. The nature of the world is such, that the same concepts differ in meaning, often so slightly, which makes it difficult to relate these concepts. It is the omni-present heterogeneity that is at the core of the web. The research work presented in this dissertation, is driven by the goal of providing a robust ontology alignment language for the semantic web, as we show that description logics based alignment languages are not suitable for aligning ontologies.

The adoption of the semantic web technologies …

Orthogonal Moment-Based Human Shape Query And Action Recognition From 3d Point Cloud Patches, Huaining Cheng

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With the recent proliferation of 3D sensors such as Light Detection and Ranging (LIDAR), it is essential to develop feature representation methods that can best characterize the point clouds produced by these devices. When these devices are employed in targeting and surveillance of human actions from both ground and aerial platforms, the corresponding point clouds of body shape often comprise low-resolution, disjoint, and irregular patches of points resulted from self-occlusions and viewing angle variations. The prevailing method of depth image analysis has the limitation of relying on 2D features that are not native representation of 3D spatial relationships. On the …

Ontology Pattern-Based Data Integration, Adila Alfa Krisnadhi

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Data integration is concerned with providing a unified access to data residing at multiple sources. Such a unified access is realized by having a global schema and a set of mappings between the global schema and the local schemas of each data source, which specify how user queries at the global schema can be translated into queries at the local schemas. Data sources are typically developed and maintained independently, and thus, highly heterogeneous. This causes difficulties in integration because of the lack of interoperability in the aspect of architecture, data format, as well as syntax and semantics of the data. …

Learning To Rank Algorithms And Their Application In Machine Translation, Tian Xia

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In this thesis, we discuss two issues in the learning to rank area, choosing effective objective loss function, constructing effective regresstion trees in the gradient boosting framework, as well as a third issus, applying learning to rank models into statistcal machine translation. First, list-wise based learning to rank methods either directly optimize performance measures or optimize surrogate functions of performance measures that have smaller gaps between optimized losses and performance measures, thus it is generally believed that they should be able to lead to better performance than point-and pair-wise based learning to rank methods. However, in real-world applications, state-of-the-art practical …

Browser Based Visualization For Parameter Spaces Of Big Data Using Client-Server Model, Kurtis M. Glendenning

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Visualization is an important task in data analytics, as it allows researchers to view abstract patterns within the data instead of reading through extensive raw data. Allowing the ability to interact with the visualizations is an essential aspect since it provides the ability to intuitively explore data to find meaning and patterns more efficiently. Interactivity, however, becomes progressively more difficult as the size of the dataset increases. This project begins by leveraging existing web-based data visualization technologies and extends their functionality through the use of parallel processing. This methodology utilizes state-of-the-art techniques, such as Node.js, to split the visualization rendering …

Owl Query Answering Using Machine Learning, Todd Huster

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The formal semantics of the Web Ontology Language (OWL) enables automated reasoning over OWL knowledge bases, which in turn can be used for a variety of purposes including knowledge base development, querying and management. Automated reasoning is usually done by means of deductive (proof-theoretic) algorithms which are either provably sound and complete or employ approximate methods to trade some correctness for improved efficiency. As has been argued elsewhere, however, reasoning methods for the Semantic Web do not necessarily have to be based on deductive methods, and approximate reasoning using statistical or machine-learning approaches may bring improved speed while maintaining high …

Temporally Biased Search Result Snippets, J. Abhiram Tatineni

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The search engine result snippets are an important source of information for the user to obtain quick insights into the corresponding result documents. When the search terms are too general, like a person's name or a company's name, creating an appropriate snippet that effectively summarizes the document's content can be challenging owing to multiple occurrences of the search term in the top ranked documents, without a simple means to select a subset of sentences containing them to form result snippet. In web pages classified as narratives and news articles, multiple references to explicit, implicit and relative temporal expressions can be …

Design Of A Novel Low - Cost, Portable, 3d Ultrasound System With Extended Imaging Capabilities For Point-Of-Care Applications, Michail Tsakalakis

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Ultrasound Imaging (USI) or Medical Sonography (MS), as it is formally called, has been widely used in biomedical applications over the last decades. USI can provide clinicians with a thorough view of the internal parts of the human body, making use of sound waves of higher frequencies than humans can perceive. USI systems are considered highly portable and of low-cost, compared to other imaging modalities. However, despite those advantages, Ultrasound Systems (US) and especially 3D ones, have not been yet extensively utilized for Point-of-Care (POC) applications, due to numerous restrictions and artifacts that they currently present.

Hardware complexity and real-time …

Mining Behavior Of Citizen Sensor Communities To Improve Cooperation With Organizational Actors, Hemant Purohit

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Web 2.0 (social media) provides a natural platform for dynamic emergence of citizen (as) sensor communities, where the citizens generate content for sharing information and engaging in discussions. Such a citizen sensor community (CSC) has stated or implied goals that are helpful in the work of formal organizations, such as an emergency management unit, for prioritizing their response needs. This research addresses questions related to design of a cooperative system of organizations and citizens in CSC. Prior research by social scientists in a limited offline and online environment has provided a foundation for research on cooperative behavior challenges, including 'articulation' …

Anonymized Video Analysis Methods And Systems, Marjorie Skubic, James M. Keller, Fang Wang, Derek T. Anderson, Erik Stone, Robert H. Luke Iii, Tanvi Banerjee, Marilyn J. Rantz

Kno.e.sis Publications

Methods and systems for anonymized video analysis are described. In one embodiment, a first silhouette image of a person in a living unit may be accessed. The first silhouette image may be based on a first video signal recorded by a first video camera. A second silhouette image of the person in the living unit may be accessed. The second silhouette image may be of a different view of the person than the first silhouette image. The second silhouette image may be based on a second video signal recorded by a second video camera. A three-dimensional model of the person …

Protecting Web Servers From Web Robot Traffic, Derek Doran

Kno.e.sis Publications

No abstract provided.

Triad-Based Role Discovery For Large Social Systems, Derek Doran

Kno.e.sis Publications

The social role of a participant in a social system conceptualizes the circumstances under which she chooses to interact with others, making their discovery and analysis important for theoretical and practical purposes. In this paper, we propose a methodology to detect such roles by utilizing the conditional triad censuses of ego-networks. These censuses are a promising tool for social role extraction because they capture the degree to which basic social forces push upon a user to interact with others in a system. Clusters of triad censuses, inferred from network samples that preserve local structural properties, define the social roles. The …

Discovering Perceptions In Online Social Media: A Probabilistic Approach, Derek Doran, Swapna S. Gokhale, Aldo Dagnino

Kno.e.sis Publications

People across the world habitually turn to online social media to share their experiences, thoughts, ideas, and opinions as they go about their daily lives. These posts collectively contain a wealth of insights into how masses perceive their surroundings. Therefore, extracting people’s perceptions from social media posts can provide valuable information about pertinent issues such as public transportation, emergency conditions, and even reactions to political actions or other activities. This paper proposes a novel approach to extract such perceptions from a corpus of social media posts originating from a given broad geographical region. The approach divides the broad region into …

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

Kno.e.sis Publications

Since the early 2000’s, Internet usage for health information searching has increased significantly. Studying search queries can help us to understand users “information need” and how do they formulate search queries (“expression of information need”). Although cardiovascular diseases (CVD) affect a large percentage of the population, few studies have investigated how and what users search for CVD. We address this knowledge gap in the community by analyzing a large corpus of 10 million CVD related search queries from MayoClinic.com. Using UMLS MetaMap and UMLS semantic types/concepts, we developed a rule-based approach to categorize the queries into 14 health categories. We …

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

Kno.e.sis Publications

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.

Distributed Owl El Reasoning: The Story So Far, Raghava Mutharaju, Pascal Hitzler, Prabhaker Mateti

Computer Science and Engineering Faculty Publications

Automated generation of axioms from streaming data, such as traffic and text, can result in very large ontologies that single machine reasoners cannot handle. Reasoning with large ontologies requires distributed solutions. Scalable reasoning techniques for RDFS, OWL Horst and OWL 2 RL now exist. For OWL 2 EL, several distributed reasoning approaches have been tried, but are all perceived to be inefficient. We analyze this perception. We analyze completion rule based distributed approaches, using different characteristics, such as dependency among the rules, implementation optimizations, how axioms and rules are distributed. We also present a distributed queue approach for the classification …

Pushing The Boundaries Of Tractable Ontology Reasoning, David Carral, Cristina Feier, Bernardo Cuenca Grau, Pascal Hitzler, Ian Horrocks

Computer Science and Engineering Faculty Publications

We identify a class of Horn ontologies for which standard reasoning tasks such as instance checking and classification are tractable. The class is general enough to include the OWL 2 EL, QL, and RL profiles. Verifying whether a Horn ontology belongs to the class can be done in polynomial time. We show empirically that the class includes many real-world ontologies that are not included in any OWL 2 profile, and thus that polynomial time reasoning is possible for these ontologies.

Data Analytics For Power Utility Storm Planning, Lan Lin, Aldo Dagnino, Derek Doran, Swapna S. Gokhale

Kno.e.sis Publications

As the world population grows, recent climatic changes seem to bring powerful storms to populated areas. The impact of these storms on utility services is devastating. Hurricane Sandy is a recent example of the enormous damages that storms can inflict on infrastructure, society, and the economy. Quick response to these emergencies represents a big challenge to electric power utilities. Traditionally utilities develop preparedness plans for storm emergency situations based on the experience of utility experts and with limited use of historical data. With the advent of the Smart Grid, utilities are incorporating automation and sensing technologies in their grids and …

A Keyword Sense Disambiguation Based Approach For Noise Filtering In Twitter, Sanjaya Wijeratne, Bahareh R. Heravi

Kno.e.sis Publications

In this paper, we describe an approach to filter out noisy data generated by keywords-based tweet filtering methods by performing Word Sense Disambiguation on those keywords used to collect tweets. We present the noise filtering problem as a binary classification problem and discuss our evaluation strategy which is to be carried out in future.

Rasp-Qs: Efficient And Confidential Query Services In The Cloud, Zohreh S. Alavi, Lu Zhou, James L. Powers, Keke Chen

Kno.e.sis Publications

Hosting data query services in public clouds is an attractive solution for its great scalability and significant cost savings. However, data owners also have concerns on data privacy due to the lost control of the infrastructure. This demonstration shows a prototype for efficient and confidential range/kNN query services built on top of the random space perturbation (RASP) method. The RASP approach provides a privacy guarantee practical to the setting of cloudbased computing, while enabling much faster query processing compared to the encryption-based approach. This demonstration will allow users to more intuitively understand the technical merits of the RASP approach via …

Metabolomics Characterization Of U.S. And Japanese F-15 And C-130 Flight Line Crews Exposed To Jet Fuel Volatile Organic Compounds And Aerosols, Nicholas J. Delraso, David Mattie, Asao Kobayashi, Stephen W. Mitchell, Scott Dillard, Michael L. Raymer, Isaie Sibomana, Nicholas V. Reo

Computer Science and Engineering Faculty Publications

Air and ground crews transfer a significant amount of jet fuel, and as a result of transfers, breathe its volatile emission from residues. Working on the flight line also exposes maintainers to exhaust from the jet fuel as engines are tested or run before and after flight. Since little is known concerning level of exposure and the corresponding biological response associated with human jet fuel exposure, nuclear magnetic resonance (NMR)-based metabolomics analysis of human urine was utilized for characterization of metabolite profiles of flight line personnel for potential biomarker discovery. This project was a collaborative research effort between the US …

Document Retrieval Using Predication Similarity, Kalpa Gunaratna

Kno.e.sis Publications

Document retrieval has been an important research problem over many years in the information retrieval community. State-of-the-art techniques utilize various methods in matching documents to a given document including keywords, phrases, and annotations. In this paper, we propose a new approach for document retrieval that utilizes predications (subject-predicate-object triples) extracted from the documents. We represent documents as sets of predications. We measure the similarity between predications to compute the similarity between documents. Our approach utilizes the hierarchical information available in ontologies in computing concept-concept similarity, making the approach flexible. Predication-based document similarity is more precise and forms the basis for …

A Novel Web-Based Depth Video Rewind Approach Toward Fall Preventive Interventions In Hospitals, Moein Enayati, Tanvi Banerjee, Mihail Popescu, Marjorie Skubic, Marilyn J. Rantz

Kno.e.sis Publications

Falls in the hospital rooms are considered a huge burden on healthcare costs. They can lead to injuries, extended length of stay, and increase in cost for both the patients and the hospital. It can also lead to emotional trauma for the patients and their families [1]. Having Microsoft Kinects installed in the hospital rooms to capture and process every movement in the room, we deployed our previously developed fall-detection system to detect naturally occurring falls, generate a real-time fall alarm and broadcast it to hospital nurses for immediate intervention. These systems also store a processed and reduced version …

Is Your Ontology As Hard As You Think? Rewriting Ontologies Into Simpler Dls, David Carral, Cristina Feier, Ana Armas Romero, Bernardo Cuenca-Grau, Pascal Hitzler, Ian Horrocks

Computer Science and Engineering Faculty Publications

We investigate cases where an ontology expressed in a seemingly hard DL can be polynomially reduced to one in a simpler logic, while preserving reasoning outcomes for classification and fact entailment. Our transformations target the elimination of inverse roles, universal and existential restrictions, and in the best case allow us to rewrite the given ontology into one of the OWL 2 profiles. Even if an ontology cannot be fully rewritten into a profile, in many cases our transformations allow us to exploit further optimisation techniques. Moreover, the elimination of some out-of-profile axioms can improve the performance of modular reasoners, such …

Accurate Local Estimation Of Geo-Coordinates For Social Media Posts, Derek Doran, Swapna S. Gokhale, Aldo Dagnino

Computer Science and Engineering Faculty Publications

Associating geo-coordinates with the content of social media posts can enhance many existing applications and services and enable a host of new ones. Unfortunately, a majority of social media posts are not tagged with geo-coordinates. Even when location data is available, it may be inaccurate, very broad or sometimes fictitious. Contemporary location estimation approaches based on analyzing the content of these posts can identify only broad areas such as a city, which limits their usefulness. To address these shortcomings, this paper proposes a methodology to narrowly estimate the geo-coordinates of social media posts with high accuracy. The methodology relies solely …

El-Ifying Ontologies, David Carral, Cristina Feier, Bernardo Cuenca Grau, Pascal Hitzler, Ian Horrocks

Computer Science and Engineering Faculty Publications

The OWL 2 profiles are fragments of the ontology language OWL 2 for which standard reasoning tasks are feasible in polynomial time. Many OWL ontologies, however, contain a typically small number of out-of-profile axioms, which may have little or no influence on reasoning outcomes. We investigate techniques for rewriting axioms into the EL and RL profiles of OWL 2. We have tested our techniques on both classification and data reasoning tasks with encouraging results.

Assisting Coordination During Crisis: A Domain Ontology Based Approach To Infer Resource Needs From Tweets, Shreyansh Bhatt, Hemant Purohit, Andrew J. Hampton, Valerie L. Shalin, Amit P. Sheth, John Flach

Kno.e.sis Publications

Ubiquitous social media during crises provides citizen reports on the situation, needs and supplies. Previous research extracts resource needs directly from the text (e.g. "Power cut to Coney Island and Brighton beach" indicates a power need). This approach assumes that citizens derive and write about specific needs from their observations, properly specified for the emergency response system, an assumption that is not consistent with general conversational behavior. In our study, Twitter messages (tweets) from Hurricane Sandy in 2012 clearly indicate power blackouts, but not their probable implications (e.g. loss of power to hospital life support systems). We use a domain …