Personalized Information Delivery: Information Filtering: Spring 2013

Instructor:

Luz M. Quiroga

School:

University of Hawaii

Semester:

Spring 2013

Description:

Reducing information overload is the main goal of Information Filtering (IF) and it has been recognized as one of the priorities in the development of current web-based information systems. IF systems are meant to deliver personalized information, acting as personal information agents that recommend relevant (filtered) documents based on their clients’ information preferences and needs (profiles).

Recommendation technology is being presented as a new paradigm of search where relevant items find the user instead of the user explicitly searching for them (http://recsys.acm.org/2009). New trends in Information technologies such as social networking and mobile devices are making personalization research and practice a priority.

Libraries have been offering personalized system in services such as: selective dissemination of information, alerting services for a long time. Customer and marketing research has also a long tradition. With the advances in information technology, personalization has evolved, now covering more sophisticated ways. Collaborative filtering, recommender systems, personalized help systems, social filtering, social data-mining systems, and user-adaptive systems can be collectively called information-filtering (IF) systems. Today, personalization is everywhere, in every industry and service, from marketing to health, travel, education, entertainment, etc.

IF researchers contend that a conceptual framework for the design of IF systems comes from two well established lines of research: Information Retrieval (IR) and User modeling (UM). The course covers theories, research and current practices in these two fields, including modeling and representation of documents, queries, user preferences, and user-system interaction.

The first part of the course includes IR models for searching: set theoretic models (e.g. Boolean model) and algebraic models (e.g. vector model). Emphasis will be given to query languages and protocols as well as to relevance feedback and strategies for query expansion and reformulation using, for example, different types of thesauri, metadata and markup languages (SGML, HTML and XML) that provide information on the document structure, format and semantics will also be included as part of the study of Web Based Information Retrieval and Filtering. Students will learn about system and user based retrieval performance evaluation and will experiment with benchmark tasks and reference test collections.

The second part of the course will mainly focus on user modeling. Although IF could be considered an application of IR, there is a major distinction: the existence of a highly individualized profile that is a representation of relatively stable user information preferences and needs. Profiles can be considered as user models and will be the center of this second part of the course which will review core topics in IF research including user modeling in IR and IF systems, acquisition of user profiles, personal ontologies, IF taxonomies, IF performance evaluation and Personal Information Management (PIM).

Required Textbook:

Baeza, R., Ribeiro-Neto, B. 2011. Modern Information Retrieval, 2nd ed.

Link to Syllabus:

http://www2.hawaii.edu/~lquiroga/courses/lis678-cis702/lis678-cis702.htm

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Database Design & Creation: Spring 2014

Instructor:

Luz M. Quiroga

School:

University of Hawaii

Semester:

Spring 2014

Description:

Behind most computerized information system there is a backend database; the performance of the system depends of how well designed the database is; understanding how a database is structured will give you knowledge to present diagrams (ER diagrams) with specifications of the data, metadata, standards, relationships, queries and reports needed.

Structuring information is the purpose of the semantic web project, one of the most important works for the future web. This project is being conducted by the inventor of the web, Tim Berners-Lee, as a way to bring order and improve finding information in the web. You will be aware of how many of the ideas in this project seem to be expansion of LIS principles for cataloging, indexing, and retrieval, applied to organization of any kind of information (e.g. booking flights, shopping, administration, health, entertainment, education, etc.)

Required Textbook:

Connolly, T., Begg, C. 2010. Database systems: a practical approach to design, implementation and management, 5th ed.

Link to Syllabus:

http://www2.hawaii.edu/~lquiroga/courses/lis674/lis674.htm

Technology for Libraries & Information Centers: Spring 2012

Instructor:

Luz. M. Quiroga

School:

University of Hawaii

Semester:

Spring 2012

Description:

Survey of theories, concepts, methods and practices relating to the application of information technology (IT) to support the administration and use of information resources. Includes digital, printed and audiovisual materials.

Required Textbook:

Kochtanek, T. R., Matthews, J. R. 2002. Library Information Systems: From Library Automation to Distributed Information Access Solutions.

Link to Syllabus:

http://www2.hawaii.edu/~lquiroga/courses/lis672/lis672syllabus.htm

Systems Analysis for Information Management: Fall 2014

Instructor:

Luz. M. Quiroga

School:

University of Hawaii

Semester:

Fall 2014

Description:

Overview of systems analysis, its techniques, benefits, and limitations. Focus on libraries and information agencies, although concepts are applicable to other settings. Structured, top-down solutions stressed throughout. Object oriented techniques and data modeling tools are reviewed.

Required Textbook:

Witten, I. H., Bainbridge, D., Nichols, D. M., 2010. How to Build a Digital Library, 2nd ed.

Link to Syllabus:

http://www.hawaii.edu/lis/content/syllabi/647_Quiroga_f2014.pdf