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Preference Top-k Search Based on Multidimensional B-tree
Ondreička, Matúš ; Pokorný, Jaroslav (advisor) ; Theobald, Martin (referee) ; Gurský, Peter (referee)
Title: Preference Top-k Search Based on Multidimensional B-Tree Author: RNDr. Matúš Ondreička Department: Department of Software Engineering Faculty of Mathematics and Physics Charles University in Prague Supervisor: Prof. RNDr. Jaroslav Pokorný, CSc. Author's e-mail address: ondreicka@ksi.mff.cuni.cz Supervisor's e-mail address: pokorny@ksi.mff.cuni.cz Abstract: In this thesis, we focus on the top-k search according to user pref- erences by using B+ -trees and the multidimensional B-tree (MDB-tree). We use model of user preferences based on fuzzy functions, which enable us to search according to a non-monotone ranking function. We propose model of sorted list based on the B+ -tree, which enables Fagin's algorithms to search for the top-k objects according to a non-monotone ranking function. We apply this model in the Internet environment with data on different remote servers. Furthermore, we designed novel dynamic tree-based data structures, namely, MDB-tree composed of B+ -trees, MDB-tree with lists, MDB-tree with groups of B+ -trees and multiple-ordered MDB-tree. Concurrently, we have developed novel top-k algorithms, namely, the MD algorithm, the MXT algorithm and their variants which are able search for the top-k objects ac- cording to a non-monotone ranking function. These top-k algorithms are efficient...
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Preferencev querying, indexing, optimisation
Horničák, Erik ; Vojtáš, Peter (advisor) ; Ondreička, Matúš (referee)
In this thesis we discuss the issue of searching the best k objects from the multi-users point of view. Every user has his own preferences, which are represented by fuzzy functions and aggregation function. This thesis designs and implements several solutions of searching the best k objects when attributes data are stored on remote servers. It was necessary to modificate existing algorithms for this type of obtaining data. This thesis uses several variants of Fagin algorithm, indexing methods using B+ trees and communication via web services.
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Acquiring user preferences for eshop
Smrčka, Zdeněk ; Vojtáš, Peter (advisor) ; Eckhardt, Alan (referee)
Title: Acquiring user preferences for e-shop Author: Zdenek Smrcka Department: The Department of Software Engineering Supervisor: prof. RNDr. Peter Vojtáš, DrSc. Abstract: The goal of this thesis is to create e-shop /in medical domain (sector), but useable in other domains (sectors)/. We use implicit metod for acquiring user preferences. By the help of this method the products are ordered from most preferred to less preferred for registered user. In case that user will choose some interesting category of products, then products are listed from maximum to less preferred in that category. It creates feedback about popularity of products for individual users and the producer gets information about interest of products in the market place and administrator can change positions of products in e-shop base on popularity. Keywords: user preferences, internet shop, user's favorite's products
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Using customer preferences in property market
Strnad, Radek ; Kopecký, Michal (advisor) ; Peška, Ladislav (referee)
In recent years the market share of major real estate companies, at least the Czech ones, has not changed much. Statistical data don't reflect any significal upward trend in volumes of properties for rent or sale. In case the real estate company would like to access larger market share, they have to secure a competitive advantage over the others. One of the ways how to attract more potential customers might be speeding up the company website's property search process. In many cases the website visitors are facing hundreds or thousands of property offers before finding couple satisfactories. The aim of the thesis is to explore possibilities of applicating customer preferences in property trading. The focus is put on research of recommender system algorithms, their characteristics and limtations. The author is evaluating usage of each algorithm variant and its suitability for a real world deployment in a real estate area. Apart from the theoretical part of the work one can find a part, where real estate information system is extended with a framework for implementing recommendation system algorithms. The author is in possesion of production data of a medium sized real estate company. He uses the recommender system framework to build and evaluate example algorithm. Powered by TCPDF (www.tcpdf.org)
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Books Recommender System via Linked Open Data
Maleček, Ladislav ; Peška, Ladislav (advisor) ; Škoda, Petr (referee)
This thesis focuses on using recommender system's methods on Linked Open Data in a domain of books. After thorough analysis of multiple available Linked Open Data sets, we have concluded that data sets of sufficient size and quality already exist. Together with careful analysis of the structure and quality of the data, recommender system web application has been developed based on retrieved data from a Wikidata endpoint. The application design allows an incorporation of data from multiple sources. A novel approach for generating recommendations utilizing multi language tags extracted from Wikipedia was used. We have shown that it is possible and viable to use recommender systems on top of the Linked Open Data, but the common recommender system's algorithms have to be modified in order to deal with a huge amount of sparsity in the data.
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Content-based recommender systems
Michalko, Maria ; Peška, Ladislav (advisor) ; Vojtáš, Peter (referee)
This work deals with the issue of poviding recommendations for individual users of e-shop based on the obtained user preferences. The work includes an overview of existing recommender systems, their methods of getting user preferences, the methods of using objects' content and recommender algorithms. An integral part of this work is design and implementated for independent software component for Content-based recommendation. Component is able to receive various user preferences and various forms of object's input data. The component also contains various processing methods for implicit feedback and various methods for making recommendations. Component is written in the Java programming language and uses a PostgreSQL database. The thesis also includes experiments that was carried out with usage of component designed on datasets slantour.cz and antikvariat-ichtys.cz e-shops.
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Using customer preferences in property market
Strnad, Radek ; Kopecký, Michal (advisor) ; Peška, Ladislav (referee)
In recent years the market share of major real estate companies, at least the Czech ones, has not changed much. Statistical data don't reflect any significal upward trend in volumes of properties for rent or sale. In case the real estate company would like to access larger market share, they have to secure a competitive advantage over the others. One of the ways how to attract more potential customers might be speeding up the company website's property search process. In many cases the website visitors are facing hundreds or thousands of property offers before finding couple satisfactories. The aim of the thesis is to explore possibilities of applicating customer preferences in property trading. The focus is put on research of recommender system algorithms, their characteristics and limtations. The author is evaluating usage of each algorithm variant and its suitability for a real world deployment in a real estate area. Apart from the theoretical part of the work one can find a part, where real estate information system is extended with a framework for implementing recommendation system algorithms. The author is in possesion of production data of a medium sized real estate company. He uses the recommender system framework to build and evaluate example algorithm. Powered by TCPDF (www.tcpdf.org)
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Preference Top-k Search Based on Multidimensional B-tree
Ondreička, Matúš ; Pokorný, Jaroslav (advisor) ; Theobald, Martin (referee) ; Gurský, Peter (referee)
Title: Preference Top-k Search Based on Multidimensional B-Tree Author: RNDr. Matúš Ondreička Department: Department of Software Engineering Faculty of Mathematics and Physics Charles University in Prague Supervisor: Prof. RNDr. Jaroslav Pokorný, CSc. Author's e-mail address: ondreicka@ksi.mff.cuni.cz Supervisor's e-mail address: pokorny@ksi.mff.cuni.cz Abstract: In this thesis, we focus on the top-k search according to user pref- erences by using B+ -trees and the multidimensional B-tree (MDB-tree). We use model of user preferences based on fuzzy functions, which enable us to search according to a non-monotone ranking function. We propose model of sorted list based on the B+ -tree, which enables Fagin's algorithms to search for the top-k objects according to a non-monotone ranking function. We apply this model in the Internet environment with data on different remote servers. Furthermore, we designed novel dynamic tree-based data structures, namely, MDB-tree composed of B+ -trees, MDB-tree with lists, MDB-tree with groups of B+ -trees and multiple-ordered MDB-tree. Concurrently, we have developed novel top-k algorithms, namely, the MD algorithm, the MXT algorithm and their variants which are able search for the top-k objects ac- cording to a non-monotone ranking function. These top-k algorithms are efficient...
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Acquiring user preferences for eshop
Smrčka, Zdeněk ; Vojtáš, Peter (advisor) ; Eckhardt, Alan (referee)
Title: Acquiring user preferences for e-shop Author: Zdenek Smrcka Department: The Department of Software Engineering Supervisor: prof. RNDr. Peter Vojtáš, DrSc. Abstract: The goal of this thesis is to create e-shop /in medical domain (sector), but useable in other domains (sectors)/. We use implicit metod for acquiring user preferences. By the help of this method the products are ordered from most preferred to less preferred for registered user. In case that user will choose some interesting category of products, then products are listed from maximum to less preferred in that category. It creates feedback about popularity of products for individual users and the producer gets information about interest of products in the market place and administrator can change positions of products in e-shop base on popularity. Keywords: user preferences, internet shop, user's favorite's products
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Preferencev querying, indexing, optimisation
Horničák, Erik ; Vojtáš, Peter (advisor) ; Ondreička, Matúš (referee)
In this thesis we discuss the issue of searching the best k objects from the multi-users point of view. Every user has his own preferences, which are represented by fuzzy functions and aggregation function. This thesis designs and implements several solutions of searching the best k objects when attributes data are stored on remote servers. It was necessary to modificate existing algorithms for this type of obtaining data. This thesis uses several variants of Fagin algorithm, indexing methods using B+ trees and communication via web services.
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