Browsing by Author "Hyvönen, Eero, Prof."

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Crisp, fuzzy, and probabilistic faceted semantic search
(2010) Holi, Markus
Aalto-yliopiston teknillinen korkeakoulu | Doctoral dissertation (monograph)
This dissertation presents contributions to the development of the faceted semantic search (FSS) paradigm. First, two fundamental solutions to FSS, which have been widely used since their development are presented. The first is the projection of search facets from annotation ontologies using logical rules. The second is the logic rule-based generation of recommendation links for search items based on the semantic relations of these items. After presenting these solutions, the rest of the dissertation focuses on solving the following deficiencies of FSS: the lack of capabilities to model uncertainty, the inability to rank search results according to relevance, and the usability problems resulting from naively using annotation ontology concepts as search categories. Two sets of solutions to these problems are presented. First, a fuzzy faceted semantic search (FFSS) framework is developed, which extends the crisp set basis of FSS to fuzzy sets. This framework is based on two main ingredients: First, weighted annotations, which are used to determine the membership degrees of search items in annotation concepts. Second, fuzzy mappings of separate end-user categories onto the annotation concepts. In addition, also a probabilistic faceted semantic search (PFSS) framework was developed, which incorporates weighted annotations, modeling of uncertainty in Semantic Web taxonomies, sophisticated mappings of end-user facets onto annotation ontologies, and the combination of evidence from multiple ranking schemes. These ranking methods were empirically analyzed. According to the preliminary evaluation both ranking methods significantly improve quality of search results compared to crisp FSS. Both also outperformed a currently used heuristical ranking method. However, in the case of FFSS this difference did not reach the level of statistical significance.
Methods and applications for ontology-based recommender systems
(2010) Ruotsalo, Tuukka
Aalto-yliopiston teknillinen korkeakoulu | Doctoral dissertation (article-based)
Recommender systems are a specific type of information filtering systems used to identify a set of objects that are relevant to a user. Instead of a user actively searching for information, recommender systems provide advice to users about objects they might wish to examine. Content-based recommender systems deal with problems related to analyzing the content, making heterogeneous content interoperable, and retrieving relevant content for the user. This thesis explores ontology-based methods to reduce these problems and to evaluate the applicability of the methods in recommender systems. First, the content analysis is improved by developing an automatic annotation method that produces structured ontology-based annotations from text. Second, an event-based method is developed to enable interoperability of heterogeneous content representations. Third, methods for semantic content retrieval are developed to determine relevant objects for the user. The methods are implemented as part of recommender systems in two cultural heritage information systems: CULTURESAMPO and SMARTMUSEUM. The performance of the methods were evaluated through user studies. The results can be divided into five parts. First, the results show improvement in automatic content analysis compared to state of the art methods and achieve performance close to human annotators. Second, the results show that the event-based method developed is suitable for bridging heterogeneous content representations. Third, the retrieval methods show accurate performance compared to user opinions. Fourth, semantic distance measures are compared to study the best query expansion strategy. Finally, practical solutions are developed to enable user profiling and result clustering. The results show that ontology-based methods enable interoperability of heterogeneous knowledge representations and result in accurate recommendations. The deployment of the methods to practical recommender systems show applicability of the results in real life settings.
Methods for creating and using geospatio-temporal semantic web
(2010) Kauppinen, Tomi
Aalto-yliopiston teknillinen korkeakoulu | Doctoral dissertation (article-based)
This dissertation discusses the problems and the methods of creating and using ontologies in the area of digital cultural heritage. One of the problems is that content annotations in semantic cultural heritage portals commonly make spatiotemporal references to historical regions and places using names whose meanings are different in different times. For example, historical administrational regions such as countries, municipalities, and cities have been renamed, merged together, split into parts, and annexed or moved to and from other regions. The contribution of this dissertation to this problem is to develop methods which can be used to model, produce and utilize geospatio-temporal ontologies. The resources in geospatio-temporal ontologies can be used as annotation terms for describing content, and also for seeking information. The main point of this dissertation is to describe schemas, models and methods that produce and utilize a geospatio-temporal ontology. The schemas and the models are used as inputs for the methods. These methods generate identifiers for spatio-temporal instances, and also relationships between them. In this work, historical Finnish municipalities were modeled and geospatio-temporal descriptions for them created from a filled-up schema. Methods enriched the models by creating geospatio-temporal relationships between these temporal municipalities. The resulting collection of models are referred to as the Finnish Spatio-temporal Ontology (Suomen ajallinen paikkaontologia, SAPO). Specific relationships of the geo-spatiotemporal instances provided the basis for novel recommendation, data mining and visualization schemes. The results of the experiments were promising. For example, with the help of the ontology a user has the ability to retrieve also the content annotated to a historic region even if she searches using a contemporary name of the same or partially overlapping region. The work contributes also to modeling and reasoning about imprecise temporal intervals. A set of different measures based on analyzing two fuzzy temporal intervals are presented and evaluated in the work. The use of a combination of different measures for calculating relevance between temporal intervals was found out to perform best.
View-based user interfaces for the Semantic Web
(2010) Mäkelä, Eetu
Aalto-yliopiston teknillinen korkeakoulu | Doctoral dissertation (article-based)
This thesis explores the possibilities of using the view-based search paradigm to create intelligent user interfaces on the Semantic Web. After surveying several semantic search techniques, the view-based search paradigm is explained, and argued to fit in a valuable niche in the field. To test the argument, numerous portals with different user interfaces and data were built using the paradigm. Based on the results of these experiments, this thesis argues that the paradigm provides a strong, extensible and flexible base on which to built semantic user interfaces. Designing the actual systems to be as adaptable as possible is also discussed.