Integrating user experience into early phases of software development

The value and benefits of user experience (UX) are widely recognized in the modern world and UX is seen as an integral part of many fields. This dissertation integrates UX and understanding end users with the early phases of software development. The concept of UX is still unclear, as witnessed by more than twenty-five definitions and ongoing argument about its different aspects and attributes. This missing consensus forms a problem in creating a link between UX and software development: How to take the UX of end users into account when it is unclear for software developers what UX stands for the end users. Furthermore, currently known methods to estimate, evaluate and analyse UX during software development are biased in favor of the phases where something concrete and tangible already exists. It would be beneficial to further elaborate on UX in the beginning phases of software development. Theoretical knowledge from the fields of UX and software development is presented and linked with surveyed and analysed UX attribute information from end users and UX professionals. Composing the surveys around the identified 21 UX attributes is described and the results are analysed in conjunction with end user demographics. Finally the utilization of the gained results is explained with a proof of concept utility, the Wizard of UX, which demonstrates how UX can be integrated into early phases of software development. The process of designing, prototyping and testing this utility is an integral part of this dissertation. The analyses show statistically significant dependencies between appreciation towards UX attributes and surveyed end user demographics. In addition, tests conducted by software developers and industrial UX designer both indicate the benefits and necessity of the prototyped Wizard of UX utility. According to the conducted tests, this utility meets the requirements set for it: It provides a way for software developers to raise their know-how of UX and a possibility to consider the UX of end users with statistical user profiles during the early phases of software development. This dissertation produces new and relevant information for the UX and software development communities by demonstrating that it is possible to integrate UX as a part of the early phases of software development.

Utilisation of Statistics in Intelligent Web Applications

Web-portaalien aiheenmukaista luokittelua voidaan hyödyntää tunnistamaan käyttäjän kiinnostuksen kohteet keräämällä tilastotietoa hänen selaustottumuksistaan eri kategorioissa. Tämä diplomityö käsittelee web-sovelluksien osa-alueita, joissa kerättyä tilastotietoa voidaan hyödyntää personalisoinnissa. Yleisperiaatteet sisällön personalisoinnista, Internet-mainostamisesta ja tiedonhausta selitetään matemaattisia malleja käyttäen. Lisäksi työssä kuvaillaan yleisluontoiset ominaisuudet web-portaaleista sekä tilastotiedon keräämiseen liittyvät seikat.

Enterprise Portal as a Knowledge Management Tool in a Global Forest Products Company

Tietojohtaminen on osoittautunut nykypäivänä organisaatioiden yhdeksi suurimmaksi haasteeksi. Haasteena ei vain ole se tiedon määrä mitä tulisi hallita, vaan pikemminkin tiedonhallinta toimii yritykselle kilpailuetuna globaalissa yritysmaailmassa. Tämän työn tavoitteena on tutkia yritysportaalin soveltuvuutta tiedonhallintaan globaalissa metsäteollisuusyrityksessä. Lisäksi tavoitteena on selvittää portaalin sovittamista kullekin käyttäjäryhmälle case yrityksessä. Työn teoriaosassa on käsitelty tiedonhallinnan monimuotoisuutta ja vaikeutta kuvata sitä yksiselitteisesti. Lisäksi käyttäjäryhmien ja käyttäjäprofiilien määrittämiseen vaikuttavia seikkoja on selvitetty tässä osassa. Empiirinen osa käsittelee case-yritystä ja sen suhdetta tiedonhallintaan sekä tämän kaltaisen tiedonhallinnan työvälineen käyttöön. Työstä saatujen tulosten perusteella voidaan todeta yritysportaalin soveltuvan hyvin tiedonhallintaan monimutkaisessakin yrityksessä. Portaali muuttaa yrityksen liiketoimintaprosesseja läpinäkyvämmiksi, kun bisneskriittistä tietoa tarjotaan yhdessä paikassa.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Mobiilipalvelut koulutusorganisaation liikkuvan työn välineenä

Päijät-Hämeen koulutuskonsernissa käynnistettiin 2008 hanke liikkuvan työn ratkaisuista, johon yhtenä osa-alueena kuului henkilöstön mobiilitarpeiden tarvekartoitus ja erilaisten liikkuvaa työtä tekevien ryhmien tunnistaminen ja luokittelu. Mobiilipalvelujen tarvekartoitus toteutettiin käyttäjälähtöisenä kyselytutkimuksena koko konsernin henkilöstölle. Tämän opinnäytetyön tavoitteena oli selvittää ammattikorkeakoulun opetushenkilöstön mobiilipalvelujen tarve ja sen perusteella tunnistaa ja luokitella erilaiset käyttäjäprofiilit. Tarvekartoitusprojekti sisälsi selvityksen, jossa haluttiin saada selville eri käyttäjäryhmien mobiilaitteiden ja tietoliikenneyhteyksien tarve. Lisäksi haluttiin selvittää, missä vastaajat työskentelevät ja kiinnostus oli erityisesti siihen, miten mobiilia vastaajien työ on tällä hetkellä. Työn tuloksia tullaan hyödyntämään hankesuunnittelussa ja mobiilipalvelujen kilpailutuksessa.

Assessment of Young Learners’ English Proficiency in Bilingual Content Instruction CLIL

This applied linguistic study in the field of second language acquisition investigated the assessment practices of class teachers as well as the challenges and visions of language assessment in bilingual content instruction (CLIL) at primary level in Finnish basic education. Furthermore, pupils’ and their parents’ perceptions of language assessment and LangPerform computer simulations as an alternative, modern assessment method in CLIL contexts were examined. The study was conducted for descriptive and developmental purposes in three phases: 1) a CLIL assessment survey; 2) simulation 1; and 3) simulation 2. All phases had a varying number of participants. The population of this mixed methods study were CLIL class teachers, their pupils and the pupils’ parents. The sampling was multi-staged and based on probability and random sampling. The data were triangulated. Altogether 42 CLIL class teachers nationwide, 109 pupils from the 3rd, 4th and 5th grade as well as 99 parents from two research schools in South-Western Finland participated in the CLIL assessment survey followed by an audio-recorded theme interview of volunteers (10 teachers, 20 pupils and 7 parents). The simulation experimentations 1 and 2 produced 146 pupil and 39 parental questionnaires as well as video interviews of volunteered pupils. The data were analysed both quantitatively using percentages and numerical frequencies and qualitatively employing thematic content analysis. Based on the data, language assessment in primary CLIL is not an established practice. It largely appears to be infrequent, incidental, implicit and based on impressions rather than evidence or the curriculum. The most used assessment methods were teacher observation, bilingual tests and dialogic interaction, and the least used were portfolios, simulations and peer assessment. Although language assessment was generally perceived as important by teachers, a fifth of them did not gather assessment information systematically, and 38% scarcely gave linguistic feedback to pupils. Both pupils and parents wished to receive more information on CLIL language issues; 91% of pupils claimed to receive feedback rarely or occasionally, and 63% of them wished to get more information on their linguistic coping in CLIL subjects. Of the parents, 76% wished to receive more information on the English proficiency of their children and their linguistic development. This may be a response to indirect feedback practices identified in this study. There are several challenges related to assessment; the most notable is the lack of a CLIL curriculum, language objectives and common ground principles of assessment. Three diverse approaches to language in CLIL that appear to affect teachers’ views on language assessment were identified: instrumental (language as a tool), dual (language as a tool and object of learning) and eclectic (miscellaneous views, e.g. affective factors prioritised). LangPerform computer simulations seem to be perceived as an appropriate alternative assessment method in CLIL. It is strongly recommended that the fundamentals for assessment (curricula and language objectives) and a mutual assessment scheme should be determined and stakeholders’ knowledge base of CLIL strengthened. The principles of adequate assessment in primary CLIL are identified as well as several appropriate assessment methods suggested.

A systematic mapping study of web services discovery mechanisms

Context: Web services have been gaining popularity due to the success of service oriented architecture and cloud computing. Web services offer tremendous opportunity for service developers to publish their services and applications over the boundaries of the organization or company. However, to fully exploit these opportunities it is necessary to find efficient discovery mechanism thus, Web services discovering mechanism has attracted a considerable attention in Semantic Web research, however, there have been no literature surveys that systematically map the present research result thus overall impact of these research efforts and level of maturity of their results are still unclear. This thesis aims at providing an overview of the current state of research into Web services discovering mechanism using systematic mapping. The work is based on the papers published 2004 to 2013, and attempts to elaborate various aspects of the analyzed literature including classifying them in terms of the architecture, frameworks and methods used for web services discovery mechanism. Objective: The objective if this work is to summarize the current knowledge that is available as regards to Web service discovery mechanisms as well as to systematically identify and analyze the current published research works in order to identify different approaches presented. Method: A systematic mapping study has been employed to assess the various Web Services discovery approaches presented in the literature. Systematic mapping studies are useful for categorizing and summarizing the level of maturity research area. Results: The result indicates that there are numerous approaches that are consistently being researched and published in this field. In terms of where these researches are published, conferences are major contributing publishing arena as 48% of the selected papers were conference published papers illustrating the level of maturity of the research topic. Additionally selected 52 papers are categorized into two broad segments namely functional and non-functional based approaches taking into consideration architectural aspects and information retrieval approaches, semantic matching, syntactic matching, behavior based matching as well as QOS and other constraints.

WordNet:n hyödyntäminen tiedonhaussa

Summary: Using WordNet in information retrieval

Identification of Research Portfolio for the Development of Filtration Equipment

This piece of work which is Identification of Research Portfolio for Development of Filtration Equipment aims at presenting a novel approach to identify promising research topics in the field of design and development of filtration equipment and processes. The projected approach consists of identifying technological problems often encountered in filtration processes. The sources of information for the problem retrieval were patent documents and scientific papers that discussed filtration equipments and processes. The problem identification method adopted in this work focussed on the semantic nature of a sentence in order to generate series of subject-action-object structures. This was achieved with software called Knowledgist. List of problems often encountered in filtration processes that have been mentioned in patent documents and scientific papers were generated. These problems were carefully studied and categorized. Suggestions were made on the various classes of these problems that need further investigation in order to propose a research portfolio. The uses and importance of other methods of information retrieval were also highlighted in this work.

Sumeat käännösmenetelmät läheisten sukulaiskielten välisessä tiedonhaussa

Summary : Fuzzy translation techniques in cross-language information retrieval between closely related languages

Local Services in a Fourth Generation Mobile Network

Neljännen sukupolven mobiiliverkot kokoaa kaikki tietoliikenneverkot ja palvelut Internetin ympärille. Tämä mullistus muuttaa vanhat vertikaaliset tietoliikenneverkot joissa yhden tietoliikenneverkon palvelut ovat saatavissa vain kyseisen verkon päätelaitteille horisontaaliseksi malliksi jossa päätelaitteet käyttävät omaa verkkoansa pääsynä Internetin palveluihin. Tämä diplomityö esittelee idean paikallisista palveluista neljännen sukupolven mobiiliverkossa. Neljännen sukupolven mobiiliverkko yhdistää perinteiset televerkkojen palvelut ja Internet palvelut sekä mahdollistaa uuden tyyppisten palveluiden luonnin. TCP/IP protokollien ja Internetin evoluutio on esitelty. Laajakaistaiset, lyhyen kantaman radiotekniikat joita käytetään langattomana yhteytenä Internetiin on käsitelty. Evoluutio kohti neljännen sukupolven mobiiliverkkoja on kuvattu esittelemällä vanhat, nykyiset ja tulevat mobiiliverkot sekä niiden palvelut. Ennustukset palveluiden ja markkinoiden tulevaisuuden kehityksestä on käsitelty. Neljännen sukupolven mobiiliverkon arkkitehtuuri mahdollistaa paikalliset palvelut jotka ovat saatavilla vain yhdessä paikallisessa 4G verkossa. Paikalliset palvelut voidaan muunnella jokaiselle käyttäjälle erikseen käyttäen profiili-informaatiota ja paikkatietoa. Työssä on pohdittu paikallisten palveluiden käyttökelpoisuutta ja mahdollisuuksia käyttäen Lappeenrannan teknillisen korkeakoulun 4G projektin palvelupilotin tuloksia.

Text Classification and Indexing in IP Networks

Internet on elektronisen postin perusrakenne ja ollut tärkeä tiedonlähde akateemisille käyttäjille jo pitkään. Siitä on tullut merkittävä tietolähde kaupallisille yrityksille niiden pyrkiessä pitämään yhteyttä asiakkaisiinsa ja seuraamaan kilpailijoitansa. WWW:n kasvu sekä määrällisesti että sen moninaisuus on luonut kasvavan kysynnän kehittyneille tiedonhallintapalveluille. Tällaisia palveluja ovet ryhmittely ja luokittelu, tiedon löytäminen ja suodattaminen sekä lähteiden käytön personointi ja seuranta. Vaikka WWW:stä saatavan tieteellisen ja kaupallisesti arvokkaan tiedon määrä on huomattavasti kasvanut viime vuosina sen etsiminen ja löytyminen on edelleen tavanomaisen Internet hakukoneen varassa. Tietojen hakuun kohdistuvien kasvavien ja muuttuvien tarpeiden tyydyttämisestä on tullut monimutkainen tehtävä Internet hakukoneille. Luokittelu ja indeksointi ovat merkittävä osa luotettavan ja täsmällisen tiedon etsimisessä ja löytämisessä. Tämä diplomityö esittelee luokittelussa ja indeksoinnissa käytettävät yleisimmät menetelmät ja niitä käyttäviä sovelluksia ja projekteja, joissa tiedon hakuun liittyvät ongelmat on pyritty ratkaisemaan.

Bluetooth wireless technology based guidance system

Lyhyen kantaman langattomat kommunikaatioteknologiat tarjoavat mahdollisuuden toteuttaa erilaisia paikkasidonnaisia palveluita käyttäjille kohtuullisilla kustannuksilla. Opastejärjestelmä, joka ohjaa käyttäjän paikasta toiseen, on yksi tälläinen palvelu. Tässä työssä esitetään langattomaan Bluetooth teknologiaan perustuva opastejärjestelmä. Muita langattomia teknologioita verrataan Bluetoothiin opastejärjestelmän toteuttamisen kannalta. Erilaisia järjestelmän arkkitehtuuri vaihtoehtoja käyttäjän paikantamiseen esitellään. Paikkatietoja hyödynnetään opasteviestin muodostamisessa. Tapoja muodostaa käyttäjän reitti kahden paikan välillä toimistorakennuksessa esitetään. Työn tulos on halpa langatonta Bluetooth teknologiaa hyödyntävä opastejärjestelmä, jota voidaan käyttää myös muiden langattomien paikkasidonnaisten palveluiden tuottamiseen.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.