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Articles 1 - 5 of 5
Full-Text Articles in Library and Information Science
Citationally Enhanced Semantic Literature Based Discovery, John David Fleig
Citationally Enhanced Semantic Literature Based Discovery, John David Fleig
CCE Theses and Dissertations
We are living within the age of information. The ever increasing flow of data and publications poses a monumental bottleneck to scientific progress as despite the amazing abilities of the human mind, it is woefully inadequate in processing such a vast quantity of multidimensional information. The small bits of flotsam and jetsam that we leverage belies the amount of useful information beneath the surface. It is imperative that automated tools exist to better search, retrieve, and summarize this content. Combinations of document indexing and search engines can quickly find you a document whose content best matches your query - if …
So What Are You Going To Do With That? The Promises And Pitfalls Of Massive Data Sets, Sigrid Anderson Cordell, Melissa Gomis
So What Are You Going To Do With That? The Promises And Pitfalls Of Massive Data Sets, Sigrid Anderson Cordell, Melissa Gomis
UNL Libraries: Faculty Publications
This article takes as its case study the challenge of data sets for text mining, sources that offer tremendous promise for digital humanities (DH) methodology but present specific challenges for humanities scholars. These text sets raise a range of issues: What skills do you train humanists to have? What is the library’s role in enabling and supporting use of those materials? How do you allocate staff? Who oversees sustainability and data management? By addressing these questions through a specific use case scenario, this article shows how these questions are central to mapping out future directions for a range of library …
Novel Machine Learning Methods For Modeling Time-To-Event Data, Bhanukiran Vinzamuri
Novel Machine Learning Methods For Modeling Time-To-Event Data, Bhanukiran Vinzamuri
Wayne State University Dissertations
Predicting time-to-event from longitudinal data where different events occur at different time points is an extremely important problem in several domains such as healthcare, economics, social networks and seismology, to name a few. A unique challenge in this problem involves building predictive models from right censored data (also called as survival data). This is a phenomenon where instances whose event of interest are not yet observed within a given observation time window and are considered to be right censored. Effective models for predicting time-to-event labels from such right censored data with good accuracy can have a significant impact in these …
Automated Library Recommendation, Ferdian Thung, David Lo, Julia Lawall
Automated Library Recommendation, Ferdian Thung, David Lo, Julia Lawall
David LO
Many third party libraries are available to be downloaded and used. Using such libraries can reduce development time and make the developed software more reliable. However, developers are often unaware of suitable libraries to be used for their projects and thus they miss out on these benefits. To help developers better take advantage of the available libraries, we propose a new technique that automatically recommends libraries to developers. Our technique takes as input the set of libraries that an application currently uses, and recommends other libraries that are likely to be relevant. We follow a hybrid approach that combines association …
Automated Library Recommendation, Ferdian Thung, David Lo, Julia Lawall
Automated Library Recommendation, Ferdian Thung, David Lo, Julia Lawall
Research Collection School Of Computing and Information Systems
Many third party libraries are available to be downloaded and used. Using such libraries can reduce development time and make the developed software more reliable. However, developers are often unaware of suitable libraries to be used for their projects and thus they miss out on these benefits. To help developers better take advantage of the available libraries, we propose a new technique that automatically recommends libraries to developers. Our technique takes as input the set of libraries that an application currently uses, and recommends other libraries that are likely to be relevant. We follow a hybrid approach that combines association …