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High-performance exploration and querying of selected multi-dimensional spaces in life sciences
Kratochvíl, Miroslav ; Bednárek, David (advisor) ; Glaab, Enrico (referee) ; Svozil, Daniel (referee)
This thesis studies, implements and experiments with specific application-oriented approaches for exploring and querying multi-dimensional datasets. The first part of the thesis scrutinizes indexing of the complex space of chemical compounds, and details a design of high-performance retrieval system for small molecules. The resulting system is then utilized within a wider context of federated search in heterogeneous data and metadata related to the chemical datasets. In the second part, the thesis focuses on fast visualization and exploration of many-dimensional data that originate from single- cell cytometry. Self-organizing maps are used to derive fast methods for analysis of the datasets, and used as a base for a novel data visualization algorithm. Finally, a similar approach is utilized for highly interactive exploration of multimedia datasets. The main contributions of the thesis comprise the advancement in optimization and methods for querying the chemical data implemented in the Sachem database cartridge, the federated, SPARQL-based interface to Sachem that provides the heterogeneous search support, dimensionality reduction algorithm EmbedSOM, design and implementation of the specific EmbedSOM-backed analysis tool for flow and mass cytometry, and design and implementation of the multimedia...
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Cross-Lingual Information Retrieval in the Medical Domain
Saleh, Shadi ; Pecina, Pavel (advisor) ; Hanbury, Allan (referee) ; Kliegr, Tomáš (referee)
Cross-Lingual Information Retrieval in the Medical Domain Shadi Saleh In recent years, there has been an exponential growth of the digital content available on the Internet, which has correlated with the increasing number of non-English Internet users due to the spread of the Internet across the globe. This raises the importance of unlocking resources for those who want to look up information not limited to the languages they understand. For example, those who want to use the Internet to find medical content related to their health conditions (self-diagnosis) but they do not have access to resources in their language. Cross-Lingual Information Retrieval (CLIR) breaks the lan- guage barriers by allowing search for documents written in a language different from the query language. This thesis tackles the task of CLIR in the medical domain and investigates the two main approaches: query translation (QT) where queries are machine translated to the language of documents and document translation (DT) where documents are translated to the language of queries. We proceed with our research by employing Statistical Machine Translation (SMT) systems that are tuned for the QT approach and the DT approach in the medical domain for seven European languages (Czech, German, French, Spanish, Hungarian, Polish and Swedish) and...
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Analysis of Mobile Devices Network Communication Data
Abraham, Lukáš ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
At the beginning, the work describes DNS and SSL/TLS protocols, it mainly deals with communication between devices using these protocols. Then we'll talk about data preprocessing and data cleaning. Furthermore, the thesis deals with basic data mining techniques such as data classification, association rules, information retrieval, regression analysis and cluster analysis. The next chapter we can read something about how to identify mobile devices on the network. We will evaluate data sets that contain collected data from communication between the above mentioned protocols, which will be used in the practical part. After that, we finally get to the design of a system for analyzing network communication data. We will describe the libraries, which we used and the entire system implementation. We will perform a large number of experiments, which we will finally evaluate.
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Information Retrieval in Czech Wikipedia
Balgar, Marek ; Bartík, Vladimír (referee) ; Chmelař, Petr (advisor)
The main task of this Masters Thesis is to understand questions of information retrieval and text classifi cation. The main research is focused on the text data, the semantic dictionaries and especially the knowledges inferred from the Wikipedia. In this thesis is also described implementation of the querying system, which is based on achieved knowledges. Finally properties and possible improvements of the system are talked over.
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The Challenges of Incorporating Grey Literature Into A Scholarly Platform
Reece, Alistair
GeoScienceWorld are in the process of acquiring, converting, and loading a major content repository with a significant amount of grey literature, to be hosted alongside our existing collection of peer-reviewed journals and books in the geosciences. What happens when a traditionally scholarly content provider decides to incorporate grey literature into their online content platform? What are the challenges of preparing the content for publication and discoverability? How does the presence of grey literature in the database affect cross search? How do differing business models find a common home in a unified content platform?
Fulltext: Reece_fulltext -  PDF
Slides: Reece_presentation_CZ - PDF; Reece_presentation_EN - PDF
Video: Reece_video -  MP4
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Meeting users in their spaces: key findings on discovery to delivery
Connaway, Lynn Silipigni ; Cyr, Chris ; Gallagher, Peggy ; Hood, Erin M. ; Brannon, Brittany ; Holloway, Jay (author of presentation and video speach)
OCLC Research has been studying how individuals get their information and resources and how they engage with technology for almost two decades. We have learned that convenience often is one of the factors that most drives individuals’ decisions for getting information and resources. However, convenience is a moving target and is dependent upon the context and situation of the individual’s need. Many factors will influence the decision-making process, such as how quickly the information or resource is needed, how important that information is to the individual need, and how much effort is required to get access to the information or resource. Our findings indicate that individuals often do not consider the library as the first place to get information and sometimes do not consider libraries at all. This often is attributed to the complexity and misunderstanding of library processes for acquiring resources and to not knowing resources or options for accessing and acquiring these resources through the library. Many individuals opt for open content since it is easy to discover and readily and quickly available in full-text. We have conducted semi-structured individual interviews with undergraduate and graduate/post graduate students and faculty in Australia and the U.S. to identify how they discover, access and acquire resources and why they make these choices and decisions, including their format preferences. We also have conducted focus group interviews with resource sharing and ILL librarians in Australia and the U.S. to identify their workflows and to discuss ideas to improve these processes to better meet the needs of their users. The findings from these interviews provide ideas for enhancing the discovery to delivery experience for both users and librarians.
Fulltext: idr-1377_1_paper - PDF
Slides: idr-1377_2_presentation - PDF
Video: idr-1377_3_video - MP4
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Suggester implementation for the OpenGrok search engine
Hornáček, Adam ; Kotal, Vladimír (advisor) ; Kofroň, Jan (referee)
The suggester functionality is an important feature of modern search engines. The aim of the thesis is to implement it for the OpenGrok project. The OpenGrok search engine is based on Apache Lucene and supports its query syntax. Presented suggester implementation supports this query syntax and provides suggestions not only for prefixes but also for wildcards, regular expressions, or phrases. The implementation also takes into account the possibility of grouping queries. That means, if one query is already specified and user is typing another query, then the first query will restrict the suggestions for the second query. The promotion of specific suggestions is based on the underlying Lucene index data structure and previous searches of the users.
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