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Selecting Link Resolver And Knowledge Base Software: Implications Of Interoperability, Cyndy Chisare, Jody C. Fagan, David J. Gaines, Michael Trocchia 2017 James Madison University

Selecting Link Resolver And Knowledge Base Software: Implications Of Interoperability, Cyndy Chisare, Jody C. Fagan, David J. Gaines, Michael Trocchia

Libraries

Link resolver software and their associated knowledge bases are essential technologies for modern academic libraries. However, because of the increasing number of possible integrations involving link resolver software and knowledge bases, a library’s vendor relationships, product choices, and consortial arrangements may have the most dramatic effects on the user experience and back-end maintenance workloads. A project team at a large comprehensive university recently investigated link resolver products in an attempt to increase efficiency of back-end workflows while maintaining or improving the patron experience. The methodology used for product comparison may be useful for other libraries.


Document Classification Using Machine Learning, Ankit Basarkar 2017 San Jose State University

Document Classification Using Machine Learning, Ankit Basarkar

Master's Projects

To perform document classification algorithmically, documents need to be represented such that it is understandable to the machine learning classifier. The report discusses the different types of feature vectors through which document can be represented and later classified. The project aims at comparing the Binary, Count and TfIdf feature vectors and their impact on document classification. To test how well each of the three mentioned feature vectors perform, we used the 20-newsgroup dataset and converted the documents to all the three feature vectors. For each feature vector representation, we trained the Naïve Bayes classifier and then tested the generated ...


Reducing Query Latency For Information Retrieval, Swapnil Satish Kamble 2017 San Jose State University

Reducing Query Latency For Information Retrieval, Swapnil Satish Kamble

Master's Projects

As the world is moving towards Big Data, NoSQL (Not only SQL) databases are gaining much more popularity. Among the other advantages of NoSQL databases, one of their key advantage is that they facilitate faster retrieval for huge volumes of data, as compared to traditional relational databases. This project deals with one such popular NoSQL database, Apache HBase. It performs quite efficiently in cases of retrieving information using the rowkey (similar to a primary key in a SQL database). But, in cases where one needs to get information based on non-rowkey columns, the response latency is higher than what we ...


A Chatbot Framework For Yioop, Harika Nukala 2017 San Jose State University

A Chatbot Framework For Yioop, Harika Nukala

Master's Projects

Over the past few years, messaging applications have become more popular than Social networking sites. Instead of using a specific application or website to access some service, chatbots are created on messaging platforms to allow users to interact with companies’ products and also give assistance as needed. In this project, we designed and implemented a chatbot Framework for Yioop. The goal of the Chatbot Framework for Yioop project is to provide a platform for developers in Yioop to build and deploy chatbot applications. A chatbot is a web service that can converse with users using artificial intelligence in messaging platforms ...


Headline Generation Using Deep Neural Networks, Dhruven Vora 2017 San Jose State University

Headline Generation Using Deep Neural Networks, Dhruven Vora

Master's Projects

News headline generation is one of the important text summarization tasks. Human generated news headlines are generally intended to catch the eye rather than provide useful information. There have been many approaches to generate meaningful headlines by either using neural networks or using linguistic features. In this report, we are proposing a novel approach based on integrating Hedge Trimmer, which is a grammar based extractive summarization system with a deep neural network abstractive summarization system to generate meaningful headlines. We analyze the results against current recurrent neural network based headline generation system.


Continuous Top-K Monitoring On Document Streams, Leong Hou U, Junjie ZHANG, Kyriakos MOURATIDIS, Ye LI 2017 Singapore Management University

Continuous Top-K Monitoring On Document Streams, Leong Hou U, Junjie Zhang, Kyriakos Mouratidis, Ye Li

Research Collection School Of Information Systems

The efficient processing of document streams plays animportant role in many information filtering systems. Emerging applications,such as news update filtering and social network notifications, demandpresenting end-users with the most relevant content to their preferences. Inthis work, user preferences are indicated by a set of keywords. A centralserver monitors the document stream and continuously reports to each user thetop-k documents that are most relevant to her keywords. Our objective is tosupport large numbers of users and high stream rates, while refreshing thetop-k results almost instantaneously. Our solution abandons the traditionalfrequency-ordered indexing approach. Instead, it follows an identifier-orderingparadigm that suits better ...


Compress: A Comprehensive Framework Of Trajectory Compression In Road Networks, Yunheng HAN, Weiwei SUN, Baihua ZHENG 2017 Singapore Management University

Compress: A Comprehensive Framework Of Trajectory Compression In Road Networks, Yunheng Han, Weiwei Sun, Baihua Zheng

Research Collection School Of Information Systems

More and more advanced technologies have become available to collect and integrate an unprecedented amount of data from multiple sources, including GPS trajectories about the traces of moving objects. Given the fact that GPS trajectories are vast in size while the information carried by the trajectories could be redundant, we focus on trajectory compression in this article. As a systematic solution, we propose a comprehensive framework, namely, COMPRESS (Comprehensive Paralleled Road-Network-Based Trajectory Compression), to compress GPS trajectory data in an urban road network. In the preprocessing step, COMPRESS decomposes trajectories into spatial paths and temporal sequences, with a thorough justification ...


Mining Helpdesk Databases For Professional Development Topic Discovery, Joel T. Lowsky 2017 University of New England

Mining Helpdesk Databases For Professional Development Topic Discovery, Joel T. Lowsky

All Theses And Dissertations

This single-site, instrumental case study created and tested a methodological road map by which academic institutions can use text data mining techniques to derive technology skillset weaknesses and professional development topics from the site’s technical support helpdesk database. The methods employed were described in detail and applied to the helpdesk database of an independent, co-educational boarding high school in the northeastern United States. Standard text data mining procedures, including the formation of a wordlist (frequently occurring terms), and the creation and application of clustering (automated data grouping) and classification (automated data labeling) models generated meaningful and revealing themes from ...


Exploiting Semantic Distance In Linked Open Data For Recommendation, Sultan Dawood Alfarhood 2017 University of Arkansas, Fayetteville

Exploiting Semantic Distance In Linked Open Data For Recommendation, Sultan Dawood Alfarhood

Theses and Dissertations

The use of Linked Open Data (LOD) has been explored in recommender systems in different ways, primarily through its graphical representation. The graph structure of LOD is utilized to measure inter-resource relatedness via their semantic distance in the graph. The intuition behind this approach is that the more connected resources are to each other, the more related they are. One drawback of this approach is that it treats all inter-resource connections identically rather than prioritizing links that may be more important in semantic relatedness calculations. Another drawback of current approaches is that they only consider resources that are connected directly ...


Improving Discovery And Patron Experience Through Data Mining, Boyuan Guan, Jamie Rogers 2017 Florida International University

Improving Discovery And Patron Experience Through Data Mining, Boyuan Guan, Jamie Rogers

Works of the FIU Libraries

As information professionals, we know simple database searches are imperfect. With rich and expansive digital collections, patrons may not find content that is buried in a long list of results. So, how do we improve discovery of pertinent materials and offer serendipitous experience? Following the example of recommendation functionality in online applications like Netflix, we have developed a recommendation function for our digital library system that provides relevant content beyond the narrow scope of patrons' original search parameters. This session will outline the reasoning, methodology, and design of the recommendation system as well as preliminary results from implementation.


The Creation Of A Building Map Application For A University Setting, William T. Whitesell 2017 Liberty University

The Creation Of A Building Map Application For A University Setting, William T. Whitesell

Senior Honors Theses

The use of navigational technology in mobile and web devices has sharply increased in recent years. With the capability to create interactive maps now available, navigating in real time between locations has become possible. This is especially essential in areas and organizations experiencing rapid expansion like Liberty University (LU). Therefore, the author proposes a project to create an interactive map application (IMA) for LU’s academic buildings that is scalable and usable through both the university’s website and with a mobile application. There are several considerations that must be taken into account when creating the LU map application, such ...


Mapping Community Space And Place In Mto Wa Mbu, Tanzania Through Surveys And Gis, Jessica Craigg 2017 Georgia College and State University

Mapping Community Space And Place In Mto Wa Mbu, Tanzania Through Surveys And Gis, Jessica Craigg

Georgia College Student Research Events

Cities throughout the African continent have been developing at an unprecedented pace, many of them due to the influence of the tourism industry. This is particularly true in Tanzania, a country famous for its national parks and their draw to tourists who help provide money for development. However, the only way to get the whole story on how to spend this money is through the experiences and needs of the people themselves. This study focuses on a small town in northeastern Tanzania, Mto wa Mbu, situated near Lake Manyara National Park, and its people’s perceptions of the park and ...


Eassistant: Cognitive Assistance For Identification And Auto-Triage Of Actionable Conversations, Hamid R. Motahari Nezhad, Kalpa Gunaratna, Juan Cappi 2017 Wright State University - Main Campus

Eassistant: Cognitive Assistance For Identification And Auto-Triage Of Actionable Conversations, Hamid R. Motahari Nezhad, Kalpa Gunaratna, Juan Cappi

Kno.e.sis Publications

The browser and screen have been the main user interfaces of the Web and mobile apps. The notification mechanism is an evolution in the user interaction paradigm by keeping users updated without checking applications. Conversational agents are posed to be the next revolution in user interaction paradigms. However, without intelligence on the triage of content served by the interaction and content differentiation in applications, interaction paradigms may still place the burden of information overload on users. In this paper, we focus on the problem of intelligent identification of actionable information in the content served by applications, and in particular in ...


A Proposed Frequency-Based Feature Selection Method For Cancer Classification, Yi Pan 2017 Western Kentucky University

A Proposed Frequency-Based Feature Selection Method For Cancer Classification, Yi Pan

Masters Theses & Specialist Projects

Feature selection method is becoming an essential procedure in data preprocessing step. The feature selection problem can affect the efficiency and accuracy of classification models. Therefore, it also relates to whether a classification model can have a reliable performance. In this study, we compared an original feature selection method and a proposed frequency-based feature selection method with four classification models and three filter-based ranking techniques using a cancer dataset. The proposed method was implemented in WEKA which is an open source software. The performance is evaluated by two evaluation methods: Recall and Receiver Operating Characteristic (ROC). Finally, we found the ...


Now You See It, Now You Don't! A Study Of Content Modification Behavior In Facebook, Fuxiang CHEN, Ee-peng LIM 2017 Singapore Management University

Now You See It, Now You Don't! A Study Of Content Modification Behavior In Facebook, Fuxiang Chen, Ee-Peng Lim

Research Collection School Of Information Systems

Social media, as a major platform to disseminate information, has changed the way users and communities contribute content. In this paper, we aim to study content modifications on public Facebook pages operated by news media, community groups, and bloggers. We also study the possible reasons behind them, and their effects on user interaction. We conducted a detailed study of Content Censorship (CC) and Content Edit (CE) in Facebook using a detailed longitudinal dataset consisting of 57 public Facebook pages over 3 weeks covering 145,955 posts and 9,379,200 comments. We detected many CC and CE activities between 28 ...


On Analyzing User Topic-Specific Platform Preferences Across Multiple Social Media Sites, Roy Ka Wei LEE, Tuan Anh HOANG, Ee-peng LIM 2017 Singapore Management University

On Analyzing User Topic-Specific Platform Preferences Across Multiple Social Media Sites, Roy Ka Wei Lee, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Information Systems

Topic modeling has traditionally been studied for single text collections and applied to social media data represented in the form of text documents. With the emergence of many social media platforms, users find themselves using different social media for posting content and for social interaction. While many topics may be shared across social media platforms, users typically show preferences of certain social media platform(s) over others for certain topics. Such platform preferences may even be found at the individual level. To model social media topics as well as platform preferences of users, we propose a new topic model known ...


Learning Personalized Preference Of Strong And Weak Ties For Social Recommendation, Xin WANG, HOI, Steven C. H., Martin ESTER, Jiajun BU, Chun CHEN 2017 Singapore Management University

Learning Personalized Preference Of Strong And Weak Ties For Social Recommendation, Xin Wang, Hoi, Steven C. H., Martin Ester, Jiajun Bu, Chun Chen

Research Collection School Of Information Systems

Recent years have seen a surge of research on social recommendation techniques for improving recommender systems due to the growing influence of social networks to our daily life. The intuition of social recommendation is that users tend to show affinities with items favored by their social ties due to social influence. Despite the extensive studies, no existing work has attempted to distinguish and learn the personalized preferences between strong and weak ties, two important terms widely used in social sciences, for each individual in social recommendation. In this paper, we first highlight the importance of different types of ties in ...


An Evidence-Based Review Of Academic Web Search Engines, 2014-2016: Implications For Librarians’ Practice And Research Agenda, Jody C. Fagan 2017 James Madison University

An Evidence-Based Review Of Academic Web Search Engines, 2014-2016: Implications For Librarians’ Practice And Research Agenda, Jody C. Fagan

Libraries

Academic web search engines have become central to scholarly research. While the fitness of Google Scholar for research purposes has been examined repeatedly, Microsoft Academic and Google Books have not received much attention. Recent studies have much to tell us about the coverage and utility of Google Scholar, its coverage of the sciences, and its utility for evaluating researcher impact. But other aspects have been understudied, such as coverage of the arts and humanities, books, and non-Western, non-English publications. User research has also tapered off. A small number of articles hint at the opportunity for librarians to become expert advisors ...


Optimization Of A Reporting Process With Input From Multiple Systems, Cheri R. Freedman 2017 Western Oregon University

Optimization Of A Reporting Process With Input From Multiple Systems, Cheri R. Freedman

Student Theses, Papers and Projects (Computer Science)

This project involves the research, development, and improvement of a reporting process used to generate reports in adherence to contractual and legislative requirements. The project will review the beginning process, the proposed and implemented solutions, and the future of the project. The project addresses the goals of data quality, timeliness, and transparency throughout the paper including how they relate to the challenges, solution selection, and overall success of the project. The need for this project reflects the ongoing need for and some of the challenges that are typical of automation and systems integration in state government entities. As the role ...


Version-Sensitive Mobile App Recommendation, Da CAO, Liqiang NIE, Xiangnan HE 2017 Singapore Management University

Version-Sensitive Mobile App Recommendation, Da Cao, Liqiang Nie, Xiangnan He

Research Collection School Of Information Systems

Being part and parcel of the daily life for billions of people all over the globe, the domain of mobile Applications (Apps) is the fastest growing sector of mobile market today. Users, however, are frequently overwhelmed by the vast number of released Apps and frequently updated versions. Towards this end, we propose a novel version-sensitive mobile App recommendation framework. It is able to recommend appropriate Apps to right users by jointly exploring the version progression and dual-heterogeneous data. It is helpful for alleviating the data sparsity problem caused by version division. As a byproduct, it can be utilized to solve ...


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