Preliminary Conference Agenda

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Session Overview
Preliminary Papers 4: Preliminary Papers: Information Organization and Retrieval
Friday, 24/Mar/2017:
8:30am - 10:00am

Location: Wuchang Hall
Location: Third Floor Capacity: 150 Size: 217㎡

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Categorization of Musicology Questions from Community-based Q&A Site using Latent Dirichlet Allocation

Hengyi Fu

Florida State university, United States of America

Question & Answer sites, such as Yahoo! Answer and Stack Exchange, are widely used to look for and exchange information in different knowledge domains. Question-answer pairs extracted from social Q&A sites can be considered as query and returned results in an information retrieval system, and descriptive access points is the intermediary to connect the information needs and information. However, information seekers sometimes experienced difficulty in precisely describing access points, and relied on system-suggested metadata to search information. This study is the first attempt to perform automatic topic modeling (Latent Dirichlet Allocation) based on the text of questions and answers related to a wide range of musical topics. The analyses confirm that LDA is a very effective tool to classify textual, unstructured, music-related data and the identified topics and question types are similar to expert cataloging based on the same set of data.

Anachronism in global information systems: the cases of Catalogue of Life and Unicode

Robert D. Montoya, Seth R. Erickson

UCLA, United States of America

The Catalogue of Life and the Unicode Standard are examples of information systems that aim toward universals: the goal of the CoL is to provide a “single integrated species checklist and taxonomic hierarchy”; the goal of Unicode is to be a “universal character set” covering the world’s writing systems. In this preliminary research paper we present anachronism as a key obstacle in the design, expansion, and evolution of such systems. We highlight the preservation of concepts (of species and of writing systems) through their inclusion in these systems as an example of how such anachronisms materialize. The goal in this piece is to present a more nuanced understanding of how information and documentary systems (viz-á-viz, indexes, taxonomies, knowledge organization systems, etc.) create new, multiplicitous temporal spaces as part of their construction—knowledge that can then be applied as information professionals build these systems and subsequently evaluate their functionality and efficacy.

Query Reformulation in Accessing Library OPAC: A Comparative Study on Different Devices

Dan Wu, Renmin Bi

Wuhan University, China, People's Republic of

This paper discusses the differences in query reformulation for mobile phone, tablet and desktop devices by mining the transaction log data of a library OPAC. We aimed to analyze the impacts of different devices on user search behavior and provide constructive suggestions for the development of library OPACs on different devices. Based on transaction logs which are 9GB in size and contain 16,140,509 records of a university library OPAC, statistics is used to analyze the differences in query reformulation on different devices in terms of two aspects: query reformulation tactics and query reformulation complexity. The results found that as reformulation times increased, the differences between query reformulation among different devices decreased. Mobile-side libraries need to optimize user interfaces, for example by setting web page labels and improving input capabilities. Desk-side libraries can add more suggestive content on the interface.

Student Program Planning with Career Information

Nan Li2, Naren Suri1, Zheng Gao1, Tian Xia3, Xiaozhong Liu1, Katy Borner1

1Indiana University Bloomington; 2Dalian Maritime University; 3Renmin University

In an interdisciplinary learning environment, students are facing difficulties to locate the right education opportunities, e.g., campus courses or MOOCs, to achieve their career goals. In this study, we propose a novel student program planning problem/system. Using the system, students can input their career goals, e.g., "Software Engineer at Google", and text and graph based recommendation algorithms will suggest education opportunities that help students achieve their career goals. Preliminary results show that the proposed solution is promising in recommending the students with a personalized program or education plan.

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