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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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User preferences in the domain of web shops
Peška, Ladislav ; Vojtáš, Peter (advisor) ; Eckhardt, Alan (referee)
The goal of the thesis is first to find available information about user preferences, user feedback and their acquisition, processing, storing etc. The collected information is then used for making suggestions / advices for the creating an recommender system for the web shops (with special emphasis on implicit feedback). The following chapters introduces UPComp - our solution of the recommender system for the web shops. The UPComp is written in the programming language PHP and uses MySQL database. The thesis also includes testing of the UPComp on real-user web shop sites slantour.cz and antikvariat-ichtys.cz.
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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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Recommender systems for culture events
Vytisková, Zuzana ; Peška, Ladislav (advisor) ; Kopecký, Michal (referee)
The diploma thesis deals with the topic of recommendation in culture. In the theoretical part, it compares the recommendation of digitally available works with event recommendations, which serves as the basis for describing recommendations on the cultural portal. Further, the thesis examines the domain model as several different interconnected types of objects. Using these relations to enrich data sets allows overcoming the low data density and improving the recommendations. The paper examines two common situations of practical recommendation, general user recommendation with minimal profile and recommendation to registered users with known history. As a part of the solution, hybrid algorithms have been implemented based on the introducing content information into existing collaborative filtering methods. The results are verified in offline tests on data sets consisting of both research and real-world data. The subjective quality of the resulting recommendations was examined through a user study.
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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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Subject access at National Library of the Czech Republic, user and librarian preference
Švadlenková, Zdenka ; Balíková, Marie (advisor) ; Kovaříková, Klára (referee)
This theses deals with the issues of the subject access to the documents at National Library of the Czech Republic with focus on user and librarian preference. It comprises seven chapters, dealing successively with all aspects and activities related to the subject access and knowledge organization at the National Library of Czech Republic. The first part is devoted to the National Library, its position in the system of the Czech public libraries and its organizational structure. Particular attention is paid to the Acquisition, Bibliography and Cataloguing department. The second chapter discusses the importance and methods of content analysis, subject access and knowledge organization. Generally characterizes the types of subject retrieval languages and traditional indexing languages with emphasis on those used in the National Library. The third section concerns principles of subject access at NL with emphasis on users' accessibility. It describes new projects, which should facilitate access to provided information. Primarily it mentions authority files, conspectus, UDC. This chapter is followed by specific examples of cataloging in MARC 21 and the importance of each step for final information retrieval. Next chapters describe other activities of the department of subject access at NK as cooperation...
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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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User preferences in the domain of web shops
Peška, Ladislav ; Vojtáš, Peter (advisor) ; Eckhardt, Alan (referee)
The goal of the thesis is first to find available information about user preferences, user feedback and their acquisition, processing, storing etc. The collected information is then used for making suggestions / advices for the creating an recommender system for the web shops (with special emphasis on implicit feedback). The following chapters introduces UPComp - our solution of the recommender system for the web shops. The UPComp is written in the programming language PHP and uses MySQL database. The thesis also includes testing of the UPComp on real-user web shop sites slantour.cz and antikvariat-ichtys.cz.
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