106,237 research outputs found
Factors Affecting Web Page Similarity
Abstract. Tools that allow effective information organisation, access and navigation are becoming increasingly important on the Web. Sim-ilarity between web pages is a concept that is central to such tools. In this paper, we examine the effect that content and layout-related as-pects of web pages have on web page similarity. We consider the textual content contained within common HTML tags, the structural layout of pages, and the query terms contained within pages. Our study shows that combinations of factors can yield more promising results than individual factors, and that different aspects of web pages affect similarities between pages in a different manner. We found a number of factors that, when taken into account, can result in effective measures of similarity between web pages. Query information in particular, proved to be important for the effective organisation of web pages.
Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows
We describe a computational protocol to aid the design of small molecule and peptide drugs that target protein-protein interactions, particularly for anti-cancer therapy. To achieve this goal, we explore multiple strategies, including finding binding hot spots, incorporating chemical similarity and bioactivity data, and sampling similar binding sites from homologous protein complexes. We demonstrate how to combine existing interdisciplinary resources with examples of semi-automated workflows. Finally, we discuss several major problems, including the occurrence of drug-resistant mutations, drug promiscuity, and the design of dual-effect inhibitors.Fil: Goncearenco, Alexander. National Institutes of Health; Estados UnidosFil: Li, Minghui. Soochow University; China. National Institutes of Health; Estados UnidosFil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Shoemaker, Benjamin A. National Institutes of Health; Estados UnidosFil: Panchenko, Anna R. National Institutes of Health; Estados Unido
Discovering the Impact of Knowledge in Recommender Systems: A Comparative Study
Recommender systems engage user profiles and appropriate filtering techniques
to assist users in finding more relevant information over the large volume of
information. User profiles play an important role in the success of
recommendation process since they model and represent the actual user needs.
However, a comprehensive literature review of recommender systems has
demonstrated no concrete study on the role and impact of knowledge in user
profiling and filtering approache. In this paper, we review the most prominent
recommender systems in the literature and examine the impression of knowledge
extracted from different sources. We then come up with this finding that
semantic information from the user context has substantial impact on the
performance of knowledge based recommender systems. Finally, some new clues for
improvement the knowledge-based profiles have been proposed.Comment: 14 pages, 3 tables; International Journal of Computer Science &
Engineering Survey (IJCSES) Vol.2, No.3, August 201
CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap
After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in
multimedia search engines, we have identified and analyzed gaps within European research effort during our second year.
In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio-
economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown
of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on
requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the
community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our
Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as
National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core
technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research
challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal
challenges
Relating Web pages to enable information-gathering tasks
We argue that relationships between Web pages are functions of the user's
intent. We identify a class of Web tasks - information-gathering - that can be
facilitated by a search engine that provides links to pages which are related
to the page the user is currently viewing. We define three kinds of intentional
relationships that correspond to whether the user is a) seeking sources of
information, b) reading pages which provide information, or c) surfing through
pages as part of an extended information-gathering process. We show that these
three relationships can be productively mined using a combination of textual
and link information and provide three scoring mechanisms that correspond to
them: {\em SeekRel}, {\em FactRel} and {\em SurfRel}. These scoring mechanisms
incorporate both textual and link information. We build a set of capacitated
subnetworks - each corresponding to a particular keyword - that mirror the
interconnection structure of the World Wide Web. The scores are computed by
computing flows on these subnetworks. The capacities of the links are derived
from the {\em hub} and {\em authority} values of the nodes they connect,
following the work of Kleinberg (1998) on assigning authority to pages in
hyperlinked environments. We evaluated our scoring mechanism by running
experiments on four data sets taken from the Web. We present user evaluations
of the relevance of the top results returned by our scoring mechanisms and
compare those to the top results returned by Google's Similar Pages feature,
and the {\em Companion} algorithm proposed by Dean and Henzinger (1999).Comment: In Proceedings of ACM Hypertext 200
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