6,189 research outputs found
Strategies for image visualisation and browsing
PhDThe exploration of large information spaces has remained a challenging task even
though the proliferation of database management systems and the state-of-the art
retrieval algorithms is becoming pervasive. Signi cant research attention in the
multimedia domain is focused on nding automatic algorithms for organising digital
image collections into meaningful structures and providing high-semantic image
indices. On the other hand, utilisation of graphical and interactive methods from
information visualisation domain, provide promising direction for creating e cient
user-oriented systems for image management. Methods such as exploratory browsing
and query, as well as intuitive visual overviews of image collection, can assist
the users in nding patterns and developing the understanding of structures and
content in complex image data-sets.
The focus of the thesis is combining the features of automatic data processing
algorithms with information visualisation. The rst part of this thesis focuses on
the layout method for displaying the collection of images indexed by low-level visual
descriptors. The proposed solution generates graphical overview of the data-set as
a combination of similarity based visualisation and random layout approach.
Second part of the thesis deals with problem of visualisation and exploration for
hierarchical organisation of images. Due to the absence of the semantic information,
images are considered the only source of high-level information. The content preview
and display of hierarchical structure are combined in order to support image
retrieval. In addition to this, novel exploration and navigation methods are proposed
to enable the user to nd the way through database structure and retrieve
the content.
On the other hand, semantic information is available in cases where automatic
or semi-automatic image classi ers are employed. The automatic annotation of
image items provides what is referred to as higher-level information. This type
of information is a cornerstone of multi-concept visualisation framework which is
developed as a third part of this thesis. This solution enables dynamic generation
of user-queries by combining semantic concepts, supported by content overview and
information ltering.
Comparative analysis and user tests, performed for the evaluation of the proposed
solutions, focus on the ways information visualisation a ects the image content
exploration and retrieval; how e cient and comfortable are the users when
using di erent interaction methods and the ways users seek for information through
di erent types of database organisation
A COLLABORATIVE FILTERING APPROACH TO PREDICT WEB PAGES OF INTEREST FROMNAVIGATION PATTERNS OF PAST USERS WITHIN AN ACADEMIC WEBSITE
This dissertation is a simulation study of factors and techniques involved in designing hyperlink recommender systems that recommend to users, web pages that past users with similar navigation behaviors found interesting. The methodology involves identification of pertinent factors or techniques, and for each one, addresses the following questions: (a) room for improvement; (b) better approach, if any; and (c) performance characteristics of the technique in environments that hyperlink recommender systems operate in. The following four problems are addressed:Web Page Classification. A new metric (PageRank × Inverse Links-to-Word count ratio) is proposed for classifying web pages as content or navigation, to help in the discovery of user navigation behaviors from web user access logs. Results of a small user study suggest that this metric leads to desirable results.Data Mining. A new apriori algorithm for mining association rules from large databases is proposed. The new algorithm addresses the problem of scaling of the classical apriori algorithm by eliminating an expensive joinstep, and applying the apriori property to every row of the database. In this study, association rules show the correlation relationships between user navigation behaviors and web pages they find interesting. The new algorithm has better space complexity than the classical one, and better time efficiency under some conditionsand comparable time efficiency under other conditions.Prediction Models for User Interests. We demonstrate that association rules that show the correlation relationships between user navigation patterns and web pages they find interesting can be transformed intocollaborative filtering data. We investigate collaborative filtering prediction models based on two approaches for computing prediction scores: using simple averages and weighted averages. Our findings suggest that theweighted averages scheme more accurately computes predictions of user interests than the simple averages scheme does.Clustering. Clustering techniques are frequently applied in the design of personalization systems. We studied the performance of the CLARANS clustering algorithm in high dimensional space in relation to the PAM and CLARA clustering algorithms. While CLARA had the best time performance, CLARANS resulted in clusterswith the lowest intra-cluster dissimilarities, and so was most effective in this regard
Personalizing Interactions with Information Systems
Personalization constitutes the mechanisms and technologies necessary to customize information access to the end-user. It can be defined as the automatic adjustment of information content, structure, and presentation tailored to the individual. In this chapter, we study personalization from the viewpoint of personalizing interaction. The survey covers mechanisms for information-finding on the web, advanced information retrieval systems, dialog-based applications, and mobile access paradigms. Specific emphasis is placed on studying how users interact with an information system and how the system can encourage and foster interaction. This helps bring out the role of the personalization system as a facilitator which reconciles the user’s mental model with the underlying information system’s organization. Three tiers of personalization systems are presented, paying careful attention to interaction considerations. These tiers show how progressive levels of sophistication in interaction can be achieved. The chapter also surveys systems support technologies and niche application domains
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
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