Web of People -- Improving Search on the Web
This event took place on Friday 26 November 2010 at 11:30
Wolfgang Nejdl Learning Lab Lower Saxony [L3S], University of Hannover, Germany
More and more information is available on the Web, and the current search engines do a great job to make it accessible. Yet, optimizing for a large number of users, they usually provide good answers only to “most of us", and have yet to provide satisfying mechanisms to search for audiovisual content.
In this talk I will present ongoing work at L3S addressing these challenges. I will start by giving a brief overview of Web Science areas covered at L3S, and the main challenges we adress in these areas, with the Web of People as one important focal point of our research, as well as Web Information Management and Web Search.
In the second part of the talk, I will discuss search for audiovisual content, and how to make this content more accessible. As many of our algorithms focus on exploiting user generated information, I will discuss what kinds of tags are used for different resources and how they can help for search. Collaborative tagging has become an increasingly popular means for sharing and organizing Web resources, leading to a
huge amount of user generated metadata. These tags represent different aspects of the resources they describe and it is not obvious whether and how these tags or subsets of them can be used for search. I will present an in-depth study of tagging behavior for different kinds of resources - Web pages, music, and images. I will also discuss how to enrich existing tags through machine learning methods, to provide indexing more appropriate to user search behavior.
This event took place on Friday 26 November 2010 at 11:30
More and more information is available on the Web, and the current search engines do a great job to make it accessible. Yet, optimizing for a large number of users, they usually provide good answers only to “most of us", and have yet to provide satisfying mechanisms to search for audiovisual content.
In this talk I will present ongoing work at L3S addressing these challenges. I will start by giving a brief overview of Web Science areas covered at L3S, and the main challenges we adress in these areas, with the Web of People as one important focal point of our research, as well as Web Information Management and Web Search.
In the second part of the talk, I will discuss search for audiovisual content, and how to make this content more accessible. As many of our algorithms focus on exploiting user generated information, I will discuss what kinds of tags are used for different resources and how they can help for search. Collaborative tagging has become an increasingly popular means for sharing and organizing Web resources, leading to a
huge amount of user generated metadata. These tags represent different aspects of the resources they describe and it is not obvious whether and how these tags or subsets of them can be used for search. I will present an in-depth study of tagging behavior for different kinds of resources - Web pages, music, and images. I will also discuss how to enrich existing tags through machine learning methods, to provide indexing more appropriate to user search behavior.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Multimedia and Information Systems is...
We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
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