Browsing by Subject "Apps"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Adding apps to our collections: A pilot project
    (American Library Association, 2017) Miller, Willie; Lee, Yoo Young; Pike, Caitlin
  • Thumbnail Image
    Item
    “Oh, Snap! The State of E-Discovery as Social Media Goes Mobile via Snapchat, WhatsApp and Other Messaging Apps
    (2015-04-17) Faklaris, Cori; Hook, Sara Anne
    As the researchers will demonstrate through current cases, each new technology that generates electronically-stored information is an opportunity to trace its path through the phases of the e-discovery process, to note the legal, technological, logistical and ethical issues at each phase and to consider any special challenges that lawyers and their support teams might face. This research is particularly timely, given that the Federal Rules of Civil Procedure are being significantly revised again, based on a May 2010 conference on civil litigation at Duke University and more than 2,300 comments from interested practitioners and academics since then. Among the revised rules that will become effective on December 1, 2015, if approved by the U.S. Supreme Court and Congress, are several that directly impact electronically-stored information, including Rules 16, 26, 34 and 37, with the goal of making the e-discovery process more efficient and less burdensome and costly.
  • Thumbnail Image
    Item
    Trust-based service selection and recommendation for online software marketplaces – TruSStReMark
    (2016-12-05) Pileththuwasan Gallege, Lahiru Sandakith; Raje, Rajeev
    This dissertation proposes a framework (TruSStReMark - Trust-based Service Selection and Recommendation for Online Software Marketplaces) to model, quantify, and monitor trust of software services and to perform trust-based service selection and recommendations. It provides methods to analyze and aggregate external reviews, pertaining to specific QoS attributes, of software services by performing subjective logic-based operations. This framework, first, defines trust of a software service using theory of belief and extends the multi-level software specifications to represent the trust-based attributes. It, then, proposes enhancements to two prevalent algorithms for selecting and recommending software services from a marketplace. Finally, the performances of the enhanced selection and recommendation algorithms are improved by parallelizing them. When compared with the prevalent Content-based and Collaborative filtering-based approaches, the results show that, the TruSStReMark is able to produce better results in terms of quality measured using HR (Hit Ratio) and ARHR (Average Reciprocal Hit-Rank) metrics. In addition, the parallelized versions of the trust-based selection and recommendation algorithms improve the end-to-end runtime. The TruSStReMark will enable users to select services, which are trustworthy, from online software marketplaces and use them in composing quality-aware distributed systems.