knowledge · information · learning - Forschungszentrum L3S

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INFORMATION
iSearch – Advanced Search Technology
The Search Engine Designed Exclusively for You!
Nowadays, search engines have become the
de facto entry point to large volume information
resources, such as the WWW, enterprise
web, and individual data storage. Search tech-
Motivation
With the increasing importance of search engines as the
primary methods for accessing all types of content, L3S
Research Center is dedicated to developing innovative
search technologies. Advanced search technologies involve
issues from multiple areas: such as ranking, personalization,
text mining and spam combating etc. Therefore, the
iSearch project focuses on developing intelligent search
technologies by collectively considering different dimensions
related to the search service.
Challenges
Several important challenges, such as how to enable personalized
information access, how to exploit novel social
media data, and how to search semi-structured and structured
data, have been considered in iSearch in the past
years. In this year, new challenges have been targeted by
iSearch and include:
• Extracting true web content and filtering noise from web
pages are beneficial for optimized web search. Effective
approaches, which include heuristic models as well as
statistics models, should be examined.
• Compared with text based spam, image-based spam is
even more difficult to combat. New characteristics of
image spam should be studied.
• The presence of noise can violate the modeling assumptions
of recommendation systems. Collaborative
filtering techniques should be attack resistant.
FORSCHUNGSZENTRUM L3S L3S RESEARCH CENTER
nologies are critical to the success of search
engines. The iSearch project aims to develop
novel search algorithms to optimize existing
search engines from multiple dimensions
The iSearch project will continue its work on
creating innovative search algorithms and solutions,
by building upon its existing core competence
and maintaining L3S Research Center’s
competitiveness.
Highlights
Work in iSearch has led to various innovative solutions and
subsequently to various high quality publications at top
rated international conferences. Highlights for the year
2008 are as follows:
• A new approach to segment HTML pages, building on
methods from Quantitative Linguistics and strategies
borrowed from the area of Computer Vision. The notion
of text-density is used as a measure to identify the
individual text segments of a web page, reducing the
problem to solving a 1D-partitioning task.
• A new collaborative algorithm based on SVD which is accurate
as well as highly stable to shilling. This algorithm
exploits previously established SVD based shilling detection
algorithms, and combines it with SVD based-CF.
• Two methods for detecting image-based spam have
been developed. The first solution, which uses the visual