Personalization

personalisierungResults of queries to document search systems (Information Retrieval systems) are often sorted simply by the similarity to the query. Different similarity computations and with it different ranking methods exist, depending, e.g., on the type of the query. A major issue of the usually employed ranking methods is the neglect of user interests. Instead, the ranking is purely based on information in the document collection itself (for web search engines, e.g., based on link analysis and site popularity) and the similarity of the documents to the query. For the predominant case of a user searching for currently popular topics or highly linked pages, this provides good results. However, these methods could even inhibit the search for documents in special subjects. In this case, the user must specify the correct additional keywords that distinct his topic from the rest. Otherwise, the relevant documents will get a rather low rank.

The aim of our research is two-fold. First, we want to create user profiles based on the user interaction with the system. Second, we develop methods that are capable of integrating this information in the presentation of search results or in navigational support for accesing a data collection.

Selected Publications

Last Modification: 01.03.2018 - Contact Person:

Sie können eine Nachricht versenden an: Prof. Dr.-Ing. Andreas Nürnberger
Sicherheitsabfrage:
Captcha
 
Lösung: