Capitalizing on Information Organization and Information Visualization for a New-Generation Catalogue

Subject searching is difficult with traditional text-based online public access library catalogues (OPACs), and the next-generation discovery layers are keyword searching and result filtering tools that offer little support for subject browsing. Next-generation OPACs ignore the rich network of relations offered by controlled subject vocabulary, which can facilitate subject browsing. A new generation of OPACs could leverage existing information-organization investments and offer online searchers a novel browsing and searching environment. This is a case study of the design and development of a virtual reality subject browsing and information retrieval tool. The functional prototype shows that the Library of Congress subject headings (LCSH) can be shaped into a useful and usable tree structure serving as a visual metaphor that contains a real world collection from the domain of science and engineering. Formative tests show that users can effectively browse the LCSH tree and carve it up based on their keyword search queries. This study uses a complex information-organization structure as a defining characteristic of an OPAC that goes beyond the standard keyword search model, toward the cutting edge of online search tools.published or submitted for publicatio

How are Cookbooks Classified in Libraries? An Examination of LCSH and LCC

There is growing interest in food and cooking in the United States, and cookbooks are published on every topic. Library standards for subject analysis must accurately represent and organize cookbooks and materials on cooking. This paper describes a research project that examined the subject of cooking in the Library of Congress Subject Headings and the Library of Congress Classification using the work of Hope Olson as a framework. It examined how the subject headings and classification numbers are constructed, how they changed over time, and how national and ethnic cuisines are treated in each standard

Similarity Models in Distributional Semantics using Task Specific Information

In distributional semantics, the unsupervised learning approach has been widely used for a large number of tasks. On the other hand, supervised learning has less coverage. In this dissertation, we investigate the supervised learning approach for semantic relatedness tasks in distributional semantics. The investigation considers mainly semantic similarity and semantic classification tasks. Existing and newly-constructed datasets are used as an input for the experiments. The new datasets are constructed from thesauruses like Eurovoc. The Eurovoc thesaurus is a multilingual thesaurus maintained by the Publications Office of the European Union. The meaning of the words in the dataset is represented by using a distributional semantic approach. The distributional semantic approach collects co-occurrence information from large texts and represents the words in high-dimensional vectors. The English words are represented by using UkWaK corpus while German words are represented by using DeWaC corpus. After representing each word by the high dimensional vector, different supervised machine learning methods are used on the selected tasks. The outputs from the supervised machine learning methods are evaluated by comparing the tasks performance and accuracy with the state of the art unsupervised machine learning methods’ results. In addition, multi-relational matrix factorization is introduced as one supervised learning method in distributional semantics. This dissertation shows the multi-relational matrix factorization method as a good alternative method to integrate different sources of information of words in distributional semantics. In the dissertation, some new applications are also introduced. One of the applications is an application which analyzes a German company’s website text, and provides information about the company with a concept cloud visualization. The other applications are automatic recognition/disambiguation of the library of congress subject headings and automatic identification of synonym relations in the Dutch Parliament thesaurus applications

Hierarchical graph maps for visualization of collaborative recommender systems

In this paper we provide a method that allows the visualization of similarity relationships present between items of collaborative filtering recommender systems, as well as the relative importance of each of these. The objective is to offer visual representations of the recommender system?s set of items and of their relationships; these graphs show us where the most representative information can be found and which items are rated in a more similar way by the recommender system?s community of users. The visual representations achieved take the shape of phylogenetic trees, displaying the numerical similarity and the reliability between each pair of items considered to be similar. As a case study we provide the results obtained using the public database Movielens 1M, which contains 3900 movies

Subject access to OPACs: exploiting the capabilities of FileMaker Pro for designing a novel interface

Ever since the libraries came to being, subject access has had been a problem. More often than not, subject searches result either in no retrievals or too many records, discouraging users to proceed further. Solutions to these problems were found in improving search methods, indexing techniques, developing user friendly novel interfaces and other methods. The present work attempts to tackle the problems of subject access using an experimental online catalogue by designing a graphic front end user interface, wherein an enhanced indexing technique that is traditional classification system coupled with improved search method by providing end user thesaurus were incorporated by using Macintosh compatible software package called FileMaker Pro. The system provides subject access by three methods i.e. Class Number Search (CNS), Subject Heading Search (SHS) and Keyword Search (KWS) to cater to the needs of two different levels of users i.e. naive or ordinary level and another for the experienced or advanced level users. A cross section of the searchers were invited to evaluate the interface. On the basis of their reactions, certain recommendations were made for the improvement of the system. In the process the capabilities and limitations of FileMaker Pro were assessed and suggestions were given for its further improvement. Certain points pertaining to the further research on the subject were also recommended

Volume 30, Number 4, December 2010

Digitized December 2010 issue of the OLAC Newsletter

Proceedings of the 2011 Great Lakes Connections Conference : Discourse & Illumination, May 20-21, 2011, School of Information Studies, University of Wisconsin-Milwaukee

The 2011 Great Lakes Connections Conference was a conference for all Library and Information Science (LIS) doctoral students and candidates. It was a student-focused conference that was intended to provide an opportunity for LIS doctoral students to share and exchange ideas and research. The conference was open to all LIS doctoral students, and included both works in progress and full papers. The accepted papers and works in progress were selected through a double-blind review process

Chapter 38 Learning Analytics

In this chapter, we present an overview of the field by articulating definitions and existing models of learning analytics. Case examples of learning analytics from Asian researchers are then summarized and reported. This is followed by an exploration of the key tensions in this field. The chapter concludes with a discussion of potential areas for future research in this area

Special Libraries, Winter 1989

Volume 80, Issue 1https://scholarworks.sjsu.edu/sla_sl_1989/1000/thumbnail.jp