This thesis deals with the problem of searching of structures in large chemical compounds databases. The aim is to design and implement an efficient system that supports two basic types of search, which are identity and substructure search. This task is complicated not only by the large number of entries in databases but also by graph representation of chemical structures, for which many algorithms are hard to solve. The thesis will introduce concepts which will prove useful in solving these problems. A web service is also created as a part of the thesis in order to make the database searching available to the users.

Internet trading had became common part of life to many people. Link to that walks also publicity that step by step moves from classical media to on-line formats. Aim of this thesis is chart possibilities of marketing and publicity on the internet and apply these pieces of knowledge practically on already running e-shop.

This master's thesis focuses on the analysis, design and implementation of Electronic Commerce. The first part is devoted to Internet marketing, search engine optimization and modeling of Electronic Commerce from a theoretical point of view. The analytical part focuses on the description of the common e-commerce functionalities and meeting with some available solutions and steps for its implementation. There will be designed and implemented model of E-commerce based on theoretical and analytical knowledge. This model will serve as the basic part for future application, which fits specific customer's needs.

The thesis deals with SEO problems (Search Engine Optimization). The part of the thesis is creation of tool which analyzes web pages in multilanguage versions and results provides with appropriate educational effect for user. According the analyzing that can be also used in the regular interval it's possible to show optimization history. The tool uses Microsoft technologies, especially ASP.NET, SQL Server 2008 or Microsoft Server 2008 and is developed by Visual Studio 2010.

The purpose of this thesis is a summary of theoretical knowledge in the field of information retrieval. This document contains mathematical models that can be used for information retrieval algorithms, including how to rank them. There are also examined the specifics of image and text data. The practical part is then an implementation of the algorithm in video shots of the TRECVid 2009 dataset based on high-level features. The uniqueness of this algorithm is to use internet search engines to obtain terms similarity. The work contains a detailed description of the implemented algorithm including the process of tuning and conclusions of its testing.

Syfte: Syftet med denna studie är att öka kunskapsområdet och förståelsen kring företagens användning av sökmotoroptimering och sökmotormarknadsföring, avseende integrering med andra digitala marknadsföringskanaler. Teoretisk referensram: De teorier som använts i denna studie är Push/Pull, The 4S Web Marketing Mix Model, Integrated Marketing Communication Mix och Digital Marketing Channel Decision Model. Metod: Denna studie utgår ifrån en kvalitativ forskningsstrategi där det empiriska underlaget har samlats in genom sju semistrukturerade telefonintervjuer. Slutsatser: Syftet med att använda sökmotorer är främst för att få synlighet och nå målgruppen. Sökmotormarknadsföring används i större utsträckning för att synas när de är hög konkurrens medan sökmotoroptimering används för att förse kunder med relevant information. Studiens slutsats visar att det krävs att det utvecklas en marknadsföringsmodell som utgår ifrån att kunder idag kontrollerar köpprocessen gällande hur företag ska förse kunder med information. Huruvida sökmotormarknadsföring integreras beror på företagens mål samt hur de integrerar digitala byråer i sin verksamhet. Företag med konkreta mål kan lättare anpassa strategi i sökmotorer efter andra digitala kanaler. Företag som anlitar byråer bör integrera byråerna i den digitala strategin för att anpassa strategi i sökmotorer efter andra digitala kanaler. / Purpose: The purpose of this research is to increase the area of knowledge and understanding of companies use of search engine optimization and search engine marketing, regarding integration with other digital marketing channels. Theoretical frame of reference: The theories used in this study are Push/Pull, The 4S web Marketing Mix Model, Integrated Marketing Communication Mix and Digital Marketing Channel Decision Model. Method: This study is based on a qualitative research strategy where the empirical data has been collected through seven semi-structured telephone interviews. Conclusions: The purpose of using search engines is primarily to gain visibility and reach the target audience. Search engine marketing is used to a greater extent to be seen when there is high competition while search engine optimization is used to provide customers with relevant information. The study's conclusion shows that it is necessary to develop a marketing model that is based on customers controlling the purchasing process regarding how companies should provide customers with information. Whether search engine marketing is integrated depends on the companies' goals and how they integrate digital agencies into their operations. Companies with concrete goals can adapt strategy in search engines with other digital channels. Companies that hire agencies should integrate the agencies into the digital strategy in order to adapt the strategy in search engines with other digital channels.

For a mobile application with focus on search functionality to be able to run smoothly, it is important to provide relevant search result based on user input. This report is to investigate how to implement a search function, to provide appropriate answers. The project consists of developing a recipe application with basic functions. The focus will be towards the search algorithm, how it will be designed. To find out what users consider is relevant, a study is done with 88 participants. The results of the survey were evaluated, and remained as an underlay for what should be searchable and how to implement the search function. Creating a good search function proved to consumes a lot of time and resources. The mobile application was completed with the desired functionality, which was provided from the survey. / För att en mobilapplikation med fokus på sökfunktionalitet ska fungera väl, är det viktigt att sökfunktionen ger relevanta resultat baserat på användarens sökningar. Den här rapporten har i syfte att undersöka sökfunktionen kan implementeras för att ge relevant svar. Projektet består av att utveckla en receptapplikation med grundläggande funktionalitet, där fokus är hur sökalgoritmen ska utformas. För att ta reda på vad användare anser relevant har en undersökning gjorts med 88 deltagare. Resultatet av undersökning har utvärderats och legat som underlag för vad som ska vara sökbart samt hur denna sökfunktion bör implementeras. Att skapa en bra sökfunktion visade sig vara både resurs- och tidskrävande. Mobilapplikationen färdigställdes med önskad funktionalitet, där sökningsalternativen är baserade på vad undersökningen visade.

L'Intelligence Artificielle est présente dans tous les aspects de notre vie à l'ère du Big Data. Elle a entraîné des changements révolutionnaires dans divers secteurs, dont le commerce électronique et la finance. Dans cette thèse, nous présentons quatre applications de l'IA qui améliorent les biens et services existants, permettent l'automatisation et augmentent considérablement l'efficacité de nombreuses tâches dans les deux domaines. Tout d'abord, nous améliorons le service de recherche de produits offert par la plupart des sites de commerce électronique en utilisant un nouveau système de pondération des termes pour mieux évaluer l'importance des termes dans une requête de recherche. Ensuite, nous construisons un modèle prédictif sur les ventes quotidiennes en utilisant une approche de prévision des séries temporelles et tirons parti des résultats prévus pour classer les résultats de recherche de produits afin de maximiser les revenus d'une entreprise. Ensuite, nous proposons la difficulté de la classification des produits en ligne et analysons les solutions gagnantes, consistant en des algorithmes de classification à la pointe de la technologie, sur notre ensemble de données réelles. Enfin, nous combinons les compétences acquises précédemment à partir de la prédiction et de la classification des ventes basées sur les séries temporelles pour prédire l'une des séries temporelles les plus difficiles mais aussi les plus attrayantes : le stock. Nous effectuons une étude approfondie sur chaque titre de l'indice S&P 500 en utilisant quatre algorithmes de classification à la pointe de la technologie et nous publions des résultats très prometteurs / Artificial Intelligence has penetrated into every aspect of our lives in this era of Big Data. It has brought revolutionary changes upon various sectors including e-commerce and finance. In this thesis, we present four applications of AI which improve existing goods and services, enables automation and greatly increase the efficiency of many tasks in both domains. Firstly, we improve the product search service offered by most e-commerce sites by using a novel term weighting scheme to better assess term importance within a search query. Then we build a predictive model on daily sales using a time series forecasting approach and leverage the predicted results to rank product search results in order to maximize the revenue of a company. Next, we present the product categorization challenge we hold online and analyze the winning solutions, consisting of the state-of-the-art classification algorithms, on our real dataset. Finally, we combine skills acquired previously from time series based sales prediction and classification to predict one of the most difficult but also the most attractive time series: stock. We perform an extensive study on every single stocks of S&P 500 index using four state-of-the-art classification algorithms and report very promising results

The aim of this work was to design and implement the application that is easily, quickly and effectively able to determine the position in the www search engines based on the given World Wide Web pages and theirs key words. The application is accessible by the web interface and it enables comparison of the position statements from the archives, comparison of the graph outputs, as well as sending of PDF format files containing regular results statements. Together with the position it is stored the number of references of particular word in the search engine. Furthermore, it is possible to display also the position changes compared with the former statements. As stated above, it is possible to store the outputs in the PDF format documents and therefore it is easy to shore the entire development in your personal computer, in case online system is insufficient.

The objective of this thesis was to explore whether there are alternatives to the established search ranking algorithm Best Matching 25 (BM25) when searching for shorter documents, in particular for the search of titles. Five search engines were compared to BM25, three of them being variants of the BM25 algorithm and the other two being based on a binary independence model that does not take term frequency or length normalisation into account. The evaluation data consisted of titles of Wikipedia articles from the fair ranking track retrieved from the main conference in the field, Text REtrieval Conference (TREC), and user logs collected from user search queries from Spotify. It was found that none of the alternative models consistently outperformed the standard BM25 for a query q where the number of words in q ranges between 1 ≤ |q| ≤ 8. Yet, for shorter queries |q| ≤ 3, the binary independence model and BM25 adaptive term (BM25adpt) outperformed the standard BM25. Furthermore, a 1% increase in Mean Average Precision (MAP) score was acquired with a binary independence model and BM25adpt compared to BM25 when sampling queries from the user log data. However, because of the bias in the evaluation data together with the small percentage increase in MAP score, it was concluded that the potential benefit of using the methods explored in this thesis is not enough to justify switching from the BM25 algorithm when searching for titles. / Målet med avhandlingen var att undersöka om det finns alternativ till den vedertagna sökalgoritmen Best matching 25 (BM25) vid sökning bland kortare document, närmare bestämt vid titelsökning. Fem sökmotorer jämfördes med BM25, tre av dem var varianter av BM25 och de andra två varianter av en binär oberoende modell. Den senare modellen använder sig inte av ordfrekvens eller längdnormalisering i sin beräkning, till skillnad från de tidigare modellerna. Evalueringsdatan bestod av titlar från Wikipedia som hämtats från den främsta konferensen inom informationssökning, Text retrieval conference (TREC), och även användarloggar hämtade från användarsökningar från Spotifys datasamling. Ingen av de alternativa modellerna presterade konsekvent bättre än BM25 när antalet ord i söktexten q varierade mellan 1 ≤ |q| ≤ 8. För kortare söktexter |q| ≤ 3 kunde både en binär oberoende modell och en BM25 adaptive term-modell (BM25adpt) prestera bättre än BM25. Vidare så kunde man se en ökning på den genomsnittliga precisionen (MAP) på 1% både hos den binära oberoende modellen och BM25adpt-modellen jämfört med BM25 när flera stickprov från användarloggdatan gjordes. På grund av att evalueringsdatan har en bias tillsammans med att den potentiella ökningen av MAP endast når upp till 1% drogs slutsatsen att fördelen med att använda en annan modell inte rättfärdigar bytet från BM25 vid titelsökning.