Content-Based Book Recommending Using Learning for Text Categorization

Recommender systems improve access to relevant products and information by making personalized suggestions based on previous examples of a user's likes and dislikes. Most existing recommender systems use social filtering methods that base recommendations on other users' preferences. By contrast, content-based methods use information about an item itself to make suggestions. This approach has the advantage of being able to recommended previously unrated items to users with unique interests and to provide explanations for its recommendations. We describe a content-based book recommending system that utilizes information extraction and a machine-learning algorithm for text categorization. Initial experimental results demonstrate that this approach can produce accurate recommendations.Comment: 8 pages, 3 figures, Submission to Fourth ACM Conference on Digital Librarie

Measuring third party tracker power across web and mobile

Third-party networks collect vast amounts of data about users via web sites and mobile applications. Consolidations among tracker companies can significantly increase their individual tracking capabilities, prompting scrutiny by competition regulators. Traditional measures of market share, based on revenue or sales, fail to represent the tracking capability of a tracker, especially if it spans both web and mobile. This paper proposes a new approach to measure the concentration of tracking capability, based on the reach of a tracker on popular websites and apps. Our results reveal that tracker prominence and parent-subsidiary relationships have significant impact on accurately measuring concentration

Coauthor prediction for junior researchers

Research collaboration can bring in different perspectives and generate more productive results. However, finding an appropriate collaborator can be difficult due to the lacking of sufficient information. Link prediction is a related technique for collaborator discovery; but its focus has been mostly on the core authors who have relatively more publications. We argue that junior researchers actually need more help in finding collaborators. Thus, in this paper, we focus on coauthor prediction for junior researchers. Most of the previous works on coauthor prediction considered global network feature and local network feature separately, or tried to combine local network feature and content feature. But we found a significant improvement by simply combing local network feature and global network feature. We further developed a regularization based approach to incorporate multiple features simultaneously. Experimental results demonstrated that this approach outperformed the simple linear combination of multiple features. We further showed that content features, which were proved to be useful in link prediction, can be easily integrated into our regularization approach. © 2013 Springer-Verlag

CC-interop : COPAC/Clumps Continuing Technical Cooperation. Final Project Report

As far as is known, CC-interop was the first project of its kind anywhere in the world and still is. Its basic aim was to test the feasibility of cross-searching between physical and virtual union catalogues, using COPAC and the three functioning "clumps" or virtual union catalogues (CAIRNS, InforM25, and RIDING), all funded or part-funded by JISC in recent years. The key issues investigated were technical interoperability of catalogues, use of collection level descriptions to search union catalogues dynamically, quality of standards in cataloguing and indexing practices, and usability of union catalogues for real users. The conclusions of the project were expected to, and indeed do, contribute to the development of the JISC Information Environment and to the ongoing debate as to the feasibility and desirability of creating a national UK catalogue. They also inhabit the territory of collection level descriptions (CLDs) and the wider services of JISC's Information Environment Services Registry (IESR). The results of this project will also have applicability for the common information environment, particularly through the landscaping work done via SCONE/CAIRNS. This work is relevant not just to HE and not just to digital materials, but encompasses other sectors and domains and caters for print resources as well. Key findings are thematically grouped as follows: System performance when inter-linking COPAC and the Z39.50 clumps. The various individual Z39.50 configurations permit technical interoperability relatively easily but only limited semantic interoperability is possible. Disparate cataloguing and indexing practices are an impairment to semantic interoperability, not just for catalogues but also for CLDs and descriptions of services (like those constituting JISC's IESR). Creating dynamic landscaping through CLDs: routines can be written to allow collection description databases to be output in formats that other UK users of CLDs, including developers of the JISC information environment. Searching a distributed (virtual) catalogue or clump via Z39.50: use of Z39.50 to Z39.50 middleware permits a distributed catalogue to be searched via Z39.50 from such disparate user services as another virtual union catalogue or clump, a physical union catalogue like COPAC, an individual Z client and other IE services. The breakthrough in this Z39.50 to Z39.50 conundrum came with the discovery that the JISC-funded JAFER software (a result of the 5/99 programme) meets many of the requirements and can be used by the current clumps services. It is technically possible for the user to select all or a sub-set of available end destination Z39.50 servers (we call this "landscaping") within this middleware. Comparing results processing between COPAC and clumps. Most distributed services (clumps) do not bring back complete results sets from associated Z servers (in order to save time for users). COPAC on-the-fly routines could feasibly be applied to the clumps services. An automated search set up to repeat its query of 17 catalogues in a clump (InforM25) hourly over nearly 3 months returned surprisingly good results; for example, over 90% of responses were received in less than one second, and no servers showed slower response times in periods of traditionally heavy OPAC use (mid-morning to early evening). User behaviour when cross-searching catalogues: the importance to users of a number of on-screen features, including the ability to refine a search and clear indication that a search is processing. The importance to users of information about the availability of an item as well as the holdings data. The impact of search tools such as Google and Amazon on user behaviour and the expectations of more information than is normally available from a library catalogue. The distrust of some librarians interviewed of the data sources in virtual union catalogues, thinking that there was not true interoperability