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- Twitter (4)
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- Crisis Response Coordination (2)
- Emergency Response (2)
- Free Energy Change (2)
- Interfacial Residue (2)
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- Kno.e.sis Publications (24)
- Harold W. Manter Laboratory of Parasitology: Faculty and Staff Publications (2)
- Research Collection School Of Computing and Information Systems (2)
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- Department of Chemical and Biomolecular Engineering: Faculty Publications (1)
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Articles 1 - 30 of 36
Full-Text Articles in Physical Sciences and Mathematics
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
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
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
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 …
An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak
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.
Discovering Perceptions In Online Social Media: A Probabilistic Approach, Derek Doran, Swapna S. Gokhale, Aldo Dagnino
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
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 …
Data Analytics For Power Utility Storm Planning, Lan Lin, Aldo Dagnino, Derek Doran, Swapna S. Gokhale
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 …
Evaluation Of Microarray-Based Dna Methylation Measurement Using Technical Replicates: The Atherosclerosis Risk In Communities (Aric) Study, Maitreyee Bose, Chong Wu, James S. Pankow, Ellen W. Demerath, Jan Bressler, Myriam Fornage, Megan L. Grove, Thomas H. Mosley, Chindo Hicks, Kari North, Wen Hong Kao, Yu Zhang, Eric Boerwinkle, Weihua Guan
Evaluation Of Microarray-Based Dna Methylation Measurement Using Technical Replicates: The Atherosclerosis Risk In Communities (Aric) Study, Maitreyee Bose, Chong Wu, James S. Pankow, Ellen W. Demerath, Jan Bressler, Myriam Fornage, Megan L. Grove, Thomas H. Mosley, Chindo Hicks, Kari North, Wen Hong Kao, Yu Zhang, Eric Boerwinkle, Weihua Guan
Computer Science Faculty Publications
Background: DNA methylation is a widely studied epigenetic phenomenon; alterations in methylation patterns influence human phenotypes and risk of disease. As part of the Atherosclerosis Risk in Communities (ARIC) study, the Illumina Infinium HumanMethylation450 (HM450) BeadChip was used to measure DNA methylation in peripheral blood obtained from ~3000 African American study participants. Over 480,000 cytosine-guanine (CpG) dinucleotide sites were surveyed on the HM450 BeadChip. To evaluate the impact of technical variation, 265 technical replicates from 130 participants were included in the study.
Results: For each CpG site, we calculated the intraclass correlation coefficient (ICC) to compare variation of methylation levels …
A Keyword Sense Disambiguation Based Approach For Noise Filtering In Twitter, Sanjaya Wijeratne, Bahareh R. Heravi
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
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 …
Document Retrieval Using Predication Similarity, Kalpa Gunaratna
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
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 …
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
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 …
Semantics-Enhanced Geoscience Interoperability, Analytics, And Applications, Krishnaprasad Thirunarayan, Amit P. Sheth
Semantics-Enhanced Geoscience Interoperability, Analytics, And Applications, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
We present our research ideas for developing cyberinfrastructure for Geoscience applications developed in the context of the EarthCube initiative, and our NSF-sponsored work on incorporating spatial-temporal-thematic semantics for enhanced querying and feature extraction from sensor data streams.
Semantic Modelling Of Smart City Data, Stefan Bischof, Athanasios Karapantelakis, Cosmin-Septimiu Nechifor, Amit P. Sheth, Alessandra Mileo, Payam Barnaghi
Semantic Modelling Of Smart City Data, Stefan Bischof, Athanasios Karapantelakis, Cosmin-Septimiu Nechifor, Amit P. Sheth, Alessandra Mileo, Payam Barnaghi
Kno.e.sis Publications
Cities present an opportunity for rendering Web of Things-enabled services. According to the World Health Organization, population in cities will double by the middle of this century, while cities deal with increasingly pressing issues such as environmental sustainability, economic growth and citizen mobility. In this paper, we propose a discussion around the need for common semantic descriptions for smart city data to facilitate future services in "smart cities". We present examples of data that can be collected from cities, discuss issues around this data and put forward some preliminary thoughts for creating a semantic description model to describe and help …
Active Learning With Efficient Feature Weighting Methods For Improving Data Quality And Classification Accuracy, Justin Martineau, Lu Chen, Doreen Cheng, Amit P. Sheth
Active Learning With Efficient Feature Weighting Methods For Improving Data Quality And Classification Accuracy, Justin Martineau, Lu Chen, Doreen Cheng, Amit P. Sheth
Kno.e.sis Publications
Many machine learning datasets are noisy with a substantial number of mislabeled instances. This noise yields sub-optimal classification performance. In this paper we study a large, low quality annotated dataset, created quickly and cheaply using Amazon Mechanical Turk to crowdsource annotations. We describe computationally cheap feature weighting techniques and a novel non-linear distribution spreading algorithm that can be used to iteratively and interactively correcting mislabeled instances to significantly improve annotation quality at low cost. Eight different emotion extraction experiments on Twitter data demonstrate that our approach is just as effective as more computationally expensive techniques. Our techniques save a considerable …
Mining Contrast Subspaces, Lei Duan, Guanting Tang, Jian Pei, James Bailey, Guozhu Dong, Akiko Campbell, Changjie Tang
Mining Contrast Subspaces, Lei Duan, Guanting Tang, Jian Pei, James Bailey, Guozhu Dong, Akiko Campbell, Changjie Tang
Kno.e.sis Publications
In this paper, we tackle a novel problem of mining contrast subspaces. Given a set of multidimensional objects in two classes C+ and C− and a query object o, we want to find top-k subspaces S that maximize the ratio of likelihood of o in C+ against that in C−. We demonstrate that this problem has important applications, and at the same time, is very challenging. It even does not allow polynomial time approximation. We present CSMiner, a mining method with various pruning techniques. CSMiner is substantially faster than the baseline method. Our …
With Whom To Coordinate, Why And How In Ad-Hoc Social Media Communications During Crisis Response, Hemant Purohit, Shreyansh Bhatt, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach
With Whom To Coordinate, Why And How In Ad-Hoc Social Media Communications During Crisis Response, Hemant Purohit, Shreyansh Bhatt, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach
Kno.e.sis Publications
During crises affected people, well-wishers, and observers join social media communities to discuss the event. They often share useful information relevant to response coordination, for example, specific resource needs. However, responders face the challenge of massive data overload and lack the time to monitor social media traffic for important information. Analysis shows that only a small number of event related conversations are actionable. Moreover, responders do not know which sources are trustworthy. To address these challenges, response teams may apply manual filtering methods, resulting in limited coverage and quality. We propose a framework and interface for extracting specific resource-related information …
Hierarchical Interest Graph From Tweets, Pavan Kapanipathi, Prateek Jain, Chitra Venkataramani, Amit P. Sheth
Hierarchical Interest Graph From Tweets, Pavan Kapanipathi, Prateek Jain, Chitra Venkataramani, Amit P. Sheth
Kno.e.sis Publications
Industry and researchers have identified numerous ways to monetize microblogs for personalization and recommendation. A common challenge across these different works is the identification of user interests. Although techniques have been developed to address this challenge, a flexible approach that spans multiple levels of granularity in user interests has not been forthcoming. In this work, we focus on exploiting hierarchical semantics of concepts to infer richer user interests expressed as a Hierarchical Interest Graph. To create such graphs, we utilize users' tweets to first ground potential user interests to structured background knowledge such as Wikipedia Category Graph. We then adapt …
Evaluating The Impact Of Genotype Errors On Rare Variant Tests Of Association, Kaitlyn Cook, Alejandra Benitez, Casey Fu, Nathan L. Tintle
Evaluating The Impact Of Genotype Errors On Rare Variant Tests Of Association, Kaitlyn Cook, Alejandra Benitez, Casey Fu, Nathan L. Tintle
Faculty Work Comprehensive List
The new class of rare variant tests has usually been evaluated assuming perfect genotype information. In reality, rare variant genotypes may be incorrect, and so rare variant tests should be robust to imperfect data. Errors and uncertainty in SNP genotyping are already known to dramatically impact statistical power for single marker tests on common variants and, in some cases, inflate the type I error rate. Recent results show that uncertainty in genotype calls derived from sequencing reads are dependent on several factors, including read depth, calling algorithm, number of alleles present in the sample, and the frequency at which an …
Leveraging Social Media And Web Of Data For Crisis Response Coordination, Carlos Castillo, Fernando Diaz, Hemant Purohit
Leveraging Social Media And Web Of Data For Crisis Response Coordination, Carlos Castillo, Fernando Diaz, Hemant Purohit
Kno.e.sis Publications
There is an ever increasing number of users in social media (1B+ Facebook users, 500M+ Twitter users) and ubiquitous mobile access (6B+ mobile phone subscribers) who share their observations and opinions. In addition, the Web of Data and existing knowledge bases keep on growing at a rapid pace. In this scenario, we have unprecedented opportunities to improve crisis response by extracting social signals, creating spatio-temporal mappings, performing analytics on social and Web of Data, and supporting a variety of applications. Such applications can help provide situational awareness during an emergency, improve preparedness, and assist during the rebuilding/recovery phase of a …
New Statistical Methods For Analysis Of Historical Data From Wildlife Populations, Trevor Hefley
New Statistical Methods For Analysis Of Historical Data From Wildlife Populations, Trevor Hefley
Department of Statistics: Dissertations, Theses, and Student Work
Wildlife biologists, many times with the help of ordinary citizens, have developed and maintained long-term datasets for monitoring the status of wildlife populations. These datasets can range from a collection of citizen-reported sightings of a rare species, to datasets collected by biologists using standardized methods. The commonality is that these datasets span a temporal and spatial scale that is beyond the scope of most scientific studies. Ensuring the continued persistence of wildlife populations requires predictions of the impact of human actions. Regardless if the predictions are quantitative or qualitative, the best we can do is use the past data to …
Computational Model For Survey And Trend Analysis Of Patients With Endometriosis : A Decision Aid Tool For Ebm, Salvo Reina, Vito Reina, Franco Ameglio, Mauro Costa, Alessandro Fasciani
Computational Model For Survey And Trend Analysis Of Patients With Endometriosis : A Decision Aid Tool For Ebm, Salvo Reina, Vito Reina, Franco Ameglio, Mauro Costa, Alessandro Fasciani
COBRA Preprint Series
Endometriosis is increasingly collecting worldwide attention due to its medical complexity and social impact. The European community has identified this as a “social disease”. A large amount of information comes from scientists, yet several aspects of this pathology and staging criteria need to be clearly defined on a suitable number of individuals. In fact, available studies on endometriosis are not easily comparable due to a lack of standardized criteria to collect patients’ informations and scarce definitions of symptoms. Currently, only retrospective surgical stadiation is used to measure pathology intensity, while the Evidence Based Medicine (EBM) requires shareable methods and correct …
Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li
Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li
Research Collection School Of Computing and Information Systems
Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results: This work proposes a new method, β ACV ASA , to predict the change of binding free energy after alanine mutations. β ACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector …
Comparative Trust Management With Applications: Bayesian Approaches Emphasis, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth
Comparative Trust Management With Applications: Bayesian Approaches Emphasis, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
Trust relationships occur naturally in many diverse contexts such as collaborative systems, e-commerce, interpersonal interactions, social networks, and semantic sensor web. As agents providing content and services become increasingly removed from the agents that consume them, the issue of robust trust inference and update becomes critical. There is a need to find online substitutes for traditional (direct or face-to-face) cues to derive measures of trust, and create efficient and robust systems for managing trust in order to support decision-making. Unfortunately, there is neither a universal notion of trust that is applicable to all domains nor a clear explication of its …
Cursing In English On Twitter, Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan, Amit P. Sheth
Cursing In English On Twitter, Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
Cursing is not uncommon during conversations in the physical world: 0.5% to 0.7% of all the words we speak are curse words, given that 1% of all the words are first-person plural pronouns (e.g., we, us, our). On social media, people can instantly chat with friends without face-to-face interaction, usually in a more public fashion and broadly disseminated through highly connected social network. Will these distinctive features of social media lead to a change in people's cursing behavior? In this paper, we examine the characteristics of cursing activity on a popular social media platform - Twitter, involving the analysis of …
Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li
Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li
Research Collection School Of Computing and Information Systems
Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results: This work proposes a new method, β ACV ASA , to predict the change of binding free energy after alanine mutations. β ACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector …
Location Prediction Of Twitter Users Using Wikipedia, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan
Location Prediction Of Twitter Users Using Wikipedia, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan
Kno.e.sis Publications
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 …
Information In Biological Systems And The Fluctuation Theorem, Yaşar Demirel
Information In Biological Systems And The Fluctuation Theorem, Yaşar Demirel
Department of Chemical and Biomolecular Engineering: Faculty Publications
Some critical trends in information theory, its role in living systems and utilization in fluctuation theory are discussed. The mutual information of thermodynamic coupling is incorporated into the generalized fluctuation theorem by using information theory and nonequilibrium thermodynamics. Thermodynamically coupled dissipative structures in living systems are capable of degrading more energy, and processing complex information through developmental and environmental constraints. The generalized fluctuation theorem can quantify the hysteresis observed in the amount of the irreversible work in nonequilibrium regimes in the presence of information and thermodynamic coupling.
What Information About Cardiovascular Diseases Do People Search Online?, Ashutosh Sopan Jadhav, Stephen Wu, Amit P. Sheth, Jyotishman Pathak
What Information About Cardiovascular Diseases Do People Search Online?, Ashutosh Sopan Jadhav, Stephen Wu, Amit P. Sheth, Jyotishman Pathak
Kno.e.sis Publications
The objective of this study is to understand the types of health information (health topics) that users search online for Cardiovascular Diseases, by performing categorization of health search queries (from Mayoclinic.com) using UMLS MetaMap based on UMLS concepts and semantic types.