NDLI: Personalized recommendation of related content based on automatic metadata extraction

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Personalized recommendation of related content based on automatic metadata extraction

Content Provider	ACM Digital Library
Author	Bakalov, Fedor König-Ries, Birgitta Nauerz, Andreas Welsch, Martin
Abstract	In order to efficiently use information, users often need access to additional background information. This additional information might be stored at various places, such as news websites, company directories, geographic information systems, etc. Oftentimes, in order to access these different pieces of information, the user has to launch new browser windows and direct them to appropriate resources. In our today's Web 2.0, the problem of accessing background information becomes even more prominent: Due to the large number of different users contributing, Web 2.0 sites grow quickly and, most often, in a more uncoordinated way regarding, e.g., structure and vocabulary used, than centrally controlled sites. In such an environment, finding relevant information can become a tedious task. In this paper, we propose a framework allowing for automated, user-specific annotation of content in order to enable provisioning of related information. Making use of unstructured data analysis services like UIMA or Calais, we are able to identify certain types of entities like locations, persons, etc. These entities are wrapped into semantic tags that contain machine-readable information about the entity type. The entity types are associated with applications able to provide background information or related content. A location, e.g., could be associated with Google Maps, whereas a person could be associated with the company's employee directory. However, it strongly depends on the individual user's interests and experience which additional information he deems relevant. We therefore tailor the information provided based on the User Model, which reflects the user's interests and expertise. This allows providing the user with in-place, in-context background information on those entities he is likely to be interested in as well as with recommendations to related content for those entities. It also relieves users from the tedious task of manually collecting relevant additional information. Our main concepts have been prototypically embedded within IBM's WebSphere Portal.
Starting Page	57
Ending Page	71
Page Count	15
File Format	PDF
DOI	10.1145/1463788.1463795
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-10-27
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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