Intelligent Internet Data Searching

In this thesis author approaches the problem of automated text classification, which is one of basic tasks for building Intelligent Internet Search Agent. The work discusses various approaches to solving sub-problems of automated text classification, such as feature extraction and machine learning on text sources. Author also describes her own multiword approach to feature extraction and pres-ents the results of testing this approach using linear discriminant analysis based classifier, and classifier combining unsupervised learning for etalon extraction with supervised learning using common backpropagation algorithm for multilevel perceptron.

Optimization and Applications of Large-Scale Biomedical Event Networks

The overwhelming amount and unprecedented speed of publication in the biomedical domain make it difficult for life science researchers to acquire and maintain a broad view of the field and gather all information that would be relevant for their research. As a response to this problem, the BioNLP (Biomedical Natural Language Processing) community of researches has emerged and strives to assist life science researchers by developing modern natural language processing (NLP), information extraction (IE) and information retrieval (IR) methods that can be applied at large-scale, to scan the whole publicly available biomedical literature and extract and aggregate the information found within, while automatically normalizing the variability of natural language statements. Among different tasks, biomedical event extraction has received much attention within BioNLP community recently. Biomedical event extraction constitutes the identification of biological processes and interactions described in biomedical literature, and their representation as a set of recursive event structures. The 2009–2013 series of BioNLP Shared Tasks on Event Extraction have given raise to a number of event extraction systems, several of which have been applied at a large scale (the full set of PubMed abstracts and PubMed Central Open Access full text articles), leading to creation of massive biomedical event databases, each of which containing millions of events. Sinece top-ranking event extraction systems are based on machine-learning approach and are trained on the narrow-domain, carefully selected Shared Task training data, their performance drops when being faced with the topically highly varied PubMed and PubMed Central documents. Specifically, false-positive predictions by these systems lead to generation of incorrect biomolecular events which are spotted by the end-users. This thesis proposes a novel post-processing approach, utilizing a combination of supervised and unsupervised learning techniques, that can automatically identify and filter out a considerable proportion of incorrect events from large-scale event databases, thus increasing the general credibility of those databases. The second part of this thesis is dedicated to a system we developed for hypothesis generation from large-scale event databases, which is able to discover novel biomolecular interactions among genes/gene-products. We cast the hypothesis generation problem as a supervised network topology prediction, i.e predicting new edges in the network, as well as types and directions for these edges, utilizing a set of features that can be extracted from large biomedical event networks. Routine machine learning evaluation results, as well as manual evaluation results suggest that the problem is indeed learnable. This work won the Best Paper Award in The 5th International Symposium on Languages in Biology and Medicine (LBM 2013).

Machine Learning and Clinical Text. Supporting Health Information Flow

Fluent health information flow is critical for clinical decision-making. However, a considerable part of this information is free-form text and inabilities to utilize it create risks to patient safety and cost-­effective hospital administration. Methods for automated processing of clinical text are emerging. The aim in this doctoral dissertation is to study machine learning and clinical text in order to support health information flow.First, by analyzing the content of authentic patient records, the aim is to specify clinical needs in order to guide the development of machine learning applications.The contributions are a model of the ideal information flow,a model of the problems and challenges in reality, and a road map for the technology development. Second, by developing applications for practical cases,the aim is to concretize ways to support health information flow. Altogether five machine learning applications for three practical cases are described: The first two applications are binary classification and regression related to the practical case of topic labeling and relevance ranking.The third and fourth application are supervised and unsupervised multi-class classification for the practical case of topic segmentation and labeling.These four applications are tested with Finnish intensive care patient records.The fifth application is multi-label classification for the practical task of diagnosis coding. It is tested with English radiology reports.The performance of all these applications is promising. Third, the aim is to study how the quality of machine learning applications can be reliably evaluated.The associations between performance evaluation measures and methods are addressed,and a new hold-out method is introduced.This method contributes not only to processing time but also to the evaluation diversity and quality. The main conclusion is that developing machine learning applications for text requires interdisciplinary, international collaboration. Practical cases are very different, and hence the development must begin from genuine user needs and domain expertise. The technological expertise must cover linguistics,machine learning, and information systems. Finally, the methods must be evaluated both statistically and through authentic user-feedback.

Clinical Learning Environment and Supervision. Development and Validation of the CLES Evaluation Scale

The purpose of the study is: (1) to describe how nursing students' experienced their clinical learning environment and the supervision given by staff nurses working in hospital settings; and (2) to develop and test an evaluation scale of Clinical Learning Environment and Supervision (CLES). The study has been carried out in different phases. The pilot study (n=163) explored the association between the characteristics of a ward and its evaluation as a learning environment by students. The second version of research instrument (which was developed by the results of this pilot study) were tested by an expert panel (n=9 nurse teachers) and test-retest group formed by student nurses (n=38). After this evaluative phase, the CLES was formed as the basic research instrument for this study and it was tested with the Finnish main sample (n=416). In this phase, a concurrent validity instrument (Dunn & Burnett 1995) was used to confirm the validation process of CLES. The international comparative study was made by comparing the Finnish main sample with a British sample (n=142). The international comparative study was necessary for two reasons. In the instrument developing process, there is a need to test the new instrument in some other nursing culture. Other reason for comparative international study is the reflecting the impact of open employment markets in the European Union (EU) on the need to evaluate and to integrate EU health care educational systems. The results showed that the individualised supervision system is the most used supervision model and the supervisory relationship with personal mentor is the most meaningful single element of supervision evaluated by nursing students. The ward atmosphere and the management style of ward manager are the most important environmental factors of the clinical ward. The study integrates two theoretical elements - learning environment and supervision - in developing a preliminary theoretical model. The comparative international study showed that, Finnish students were more satisfied and evaluated their clinical placements and supervision with higher scores than students in the United Kingdom (UK). The difference between groups was statistical highly significant (p= 0.000). In the UK, clinical placements were longer but students met their nurse teachers less frequently than students in Finland. Arrangements for supervision were similar. This research process has produced the evaluation scale (CLES), which can be used in research and quality assessments of clinical learning environment and supervision in Finland and in the UK. CLES consists of 27 items and it is sub-divided into five sub-dimensions. Cronbach's alpha coefficient varied from high 0.94 to marginal 0.73. CLES is a compact evaluation scale and user-friendliness makes it suitable for continuing evaluation.

Emotions in a Web-based Learning Environment

The aim of this thesis was to examine emotions in a web-based learning environment (WBLE). Theoretically, the thesis was grounded on the dimensional model of emotions. Four empirical studies were conducted. Study I focused on students’ anxiety and their self-efficacy in computer-using situations. Studies II and III examined the influence of experienced emotions on students’ collaborative visible and non-collaborative invisible activities and lurking in a WBLE. Study II also focused on the antecedents of the emotions students experience in a web-based learning environment. Study IV concentrated on clarifying the differences between emotions experienced in face-to-face and web-based collaborative learning. The results of these studies are reported in four original research articles published in scientific journals. The present studies demonstrate that emotions are important determinants of student behaviour in a web-based learning, and justify the conclusion that interactions on the web can and do have an emotional content. Based on the results of these empirical studies, it can be concluded that the emotions students experience during the web-based learning result mostly from the social interactions rather than from the technological context. The studies indicate that the technology itself is not the only antecedent of students’ emotional reactions in the collaborative web-based learning situations. However, the technology itself also exerted an influence on students’ behaviour. It was found that students’ computer anxiety was associated with their negative expectations of the consequences of using technology-based learning environments in their studies. Moreover, the results also indicated that student behaviours in a WBLE can be divided into three partially overlapping classes: i) collaborative visible ii) non-collaborative invisible activities, and iii) lurking. What is more, students’ emotions experienced during the web-based learning affected how actively they participated in such activities in the environment. Especially lurkers, i.e. students who seldom participated in discussions but frequently visited the online environment, experienced more negatively valenced emotions during the courses than did the other students. This result indicates that such negatively toned emotional experiences can make the lurking individuals less eager to participate in other WBLE courses in the future. Therefore, future research should also focus more precisely on the reasons that cause individuals to lurk in online learning groups, and the development of learning tasks that do not encourage or permit lurking or inactivity. Finally, the results from the study comparing emotional reactions in web-based and face-to-face collaborative learning indicated that the learning by means of web-based communication resulted in more affective reactivity when compared to learning in a face-to-face situation. The results imply that the students in the web-based learning group experienced more intense emotions than the students in the face-to-face learning group.The interpretations of this result are that the lack of means for expressing emotional reactions and perceiving others’ emotions increased the affectivity in the web-based learning groups. Such increased affective reactivity could, for example, debilitate individual’s learning performance, especially in complex learning tasks. Therefore, it is recommended that in the future more studies should be focused on the possibilities to express emotions in a text-based web environment to ensure better means for communicating emotions, and subsequently, possibly decrease the high level of affectivity. However, we do not yet know whether the use of means for communicating emotional expressions via the web (for example, “smileys” or “emoticons”) would be beneficial or disadvantageous in formal learning situations. Therefore, future studies should also focus on assessing how the use of such symbols as a means for expressing emotions in a text-based web environment would affect students’ and teachers’ behaviour and emotional state in web-based learning environments.

Learning in Product Development Projects - Responding to challenges in global industrial company

Verkostoitunut kansainvälinen tuotekehitys on tärkeä osa menestystä nykypäivän muuttuvassa yritysmaailmassa. Toimintojen tehostamiseksi myös projektitoiminnot on sopeutettava kansainväliseen toimintaympäristöön. Kilpailukyvyn säilyttämiseksi projektitoimintoja on lisäksi jatkuvasti tehostettava. Yhtenäkeinona nähdään projektioppiminen, jota voidaan edistää monin eri tavoin. Tässätyössä keskitytään projektitiedonhallinnan kehittämisen tuomiin oppimismahdollisuuksiin. Kirjallisuudessa kerrotaan, että projektitiedon jakaminen ja sen hyödyntäminen seuraavissa projekteissa on eräs projektioppimisen edellytyksistä. Tämäon otettu keskeiseksi näkökulmaksi tässä tutkimuksessa. Lisäksi tutkimusalueen rajaamiseksi työ tarkastelee erityisesti projektioppimista kansainvälisten tuotekehitysprojektien välillä. Työn tavoitteena on esitellä keskeisiä projektioppimisen haasteita ja etsiä konkreettinen ratkaisu vastaamaan näihin haasteisiin. Tuotekehitystoiminnot ja kansainvälinen hajautettu projektiorganisaatio kohtaavat lisäksi erityisiä haasteita, kuten tiedon hajautuneisuus, projektihenkilöstön vaihtuvuus, tiedon luottamuksellisuus ja maantieteelliset haasteet (esim. aikavyöhykkeet ja toimipisteen sijainti). Nämä erityishaasteet on otettu huomioon ratkaisua etsittäessä. Haasteisiin päädyttiin vastaamaan tietotekniikkapohjaisella ratkaisulla, joka suunniteltiin erityisesti huomioiden esimerkkiorganisaation tarpeet ja haasteet. Työssä tarkastellaan suunnitellun ratkaisun vaikutusta projektioppimiseen ja kuinka se vastaa havaittuihin haasteisiin. Tuloksissa huomattiin, että projektioppimista tapahtui, vaikka oppimista oli vaikea suoranaisesti huomata tutkimusorganisaation jäsenten keskuudessa. Projektioppimista voidaan kuitenkin sanoa tapahtuvan, jos projektitieto on helposti koko projektiryhmän saatavilla ja se on hyvin järjesteltyä. Muun muassa nämä ehdot täyttyivät. Projektioppiminen nähdään yleisesti haastavana kehitysalueena esimerkkiorganisaatiossa. Suuri osa tietämyksestä on niin sanottua hiljaistatietoa, jota on hankala tai mahdoton saattaa kirjalliseen muotoon. Näin olleen tiedon siirtäminen jää suurelta osin henkilökohtaisen vuorovaikutuksen varaan. Siitä huolimatta projektioppimista on mahdollista kehittää erilaisin toimintamallein ja menetelmin. Kehitys vaatii kuitenkin resursseja, pitkäjänteisyyttä ja aikaa. Monet muutokset voivat vaatia myös organisaatiokulttuurin muutoksen ja vaikuttamista organisaation jäseniin. Motivaatio, positiiviset mielikuvat ja selkeät strategiset tavoitteet luovat vakaan pohjan projektioppimisen kehittämiselle.

Developing Processes and Learning in a Project-based Firm

Tämän diplomityön tavoitteena on kuvata tiedonkulkua projektiliiketoimintaa harjoittavassa yrityksessä sekä analysoida kuvausta määrittäen mahdolliset kehityskohdat. Työssätuotetut kuvaukset ja kehityskohtien määrittäminen toimivat pohjana yrityksen kehittäessä projektien hallintaansa tulevaisuudessa. Työssä valitaan tietojohtamisen näkökulma sopivaksi lähestymistavaksi yrityksen toiminnananalysointiin. Haastatteluin kerätyn tutkimusmateriaalin perusteella luodaan prosessikuvaukset jotka mallintavat tietovirtoja yrityksen projektien aikana tapahtuvien prosessien välillä. Kuvausta peilataan tietämyksen luomisen sekä projektien tietojohtamisen teoriaan ja määritetään kehityskohteita. Kehityskohteiden määrittämisen lisäksi ehdotetaan mahdollisia toimenpiteitä tiedon ja tietämyksen hallinnan kehittämiseksi. Kokemusten ja opittujen asioiden sekäpalautteen kerääminen projektien aikana sekä niiden jälkeen havaittiin tärkeimmäksi kehityskohdaksi. Näiden keräämisen voidaan todeta vaativan järjestelmällisyyttä jotta projektien onnistumiset sekä niissä saavutetut parannukset voidaan toistaa jatkossa ja virheet sekä epäonnistumiset sitä vastoin välttää.

The Roles of Cultural, Functional and Value Diversity in Innovativeness and Learning

Tutkielman tavoite on tutkia kulttuurista, funktionaalista ja arvojen diversiteettiä, niiden suhdetta innovatiivisuuteen ja oppimiseen sekä tarjota keinoja diversiteetin johtamiseen. Tämän lisäksi selvitetään linjaesimiesten haastattelujen kautta miten diversiteetti case -organisaatiossa tällä hetkellä koetaan. Organisaation diversiteetin tämänhetkisen tilan tunnistamisen kautta voidaan esittää parannusehdotuksia diversiteetin hallintaan. Tutkimus- ja tiedonkeruumenetelmänä käytetään kvalitatiivista focus group haastattelumenetelmää. Tutkimuksessa saatiin selkeä kuva kulttuurisen, funktionaalisen ja arvojen diversiteetin merkityksistä organisaation innovatiivisuudelle ja oppimiselle sekä löydettiin keinoja näiden diversiteetin tyyppien johtamiseen. Tutkimuksen tärkeä löydös on se, että diversiteetti vaikuttaa positiivisesti organisaation innovatiivisuuteen kun sitä johdetaan tehokkaasti ja kun organisaatioympäristö tukee avointa keskustelua ja mielipiteiden jakamista. Case organisaation tämänhetkistä diversiteetin tilaa selvitettäessä havaittiin että ongelma organisaatiossa ei ole diversiteetin puute, vaan paremminkin se, ettei diversiteettia osata hyödyntää. Organisaatio ei tue erilaisten näkemysten ja mielipiteiden vapaata esittämistä jahyväksikäyttöä ja siksi diversiteetin hyödyntäminen on epätäydellistä. Haastatteluissa tärkeinä seikkoina diversiteetin hyödyntämisen parantamisessa nähtiin kulttuurin muuttaminen avoimempaan suuntaan ja johtajien esimiestaitojen parantaminen.

Information System ProcessInnovation Adoption, Adaptation, Learning, and Unlearning: A Longitudinal Case Study

This thesis examines the history and evolution of information system process innovation (ISPI) processes (adoption, adaptation, and unlearning) within the information system development (ISD) work in an internal information system (IS) department and in two IS software house organisations in Finland over a 43-year time-period. The study offers insights into influential actors and their dependencies in deciding over ISPIs. The research usesa qualitative research approach, and the research methodology involves the description of the ISPI processes, how the actors searched for ISPIs, and how the relationships between the actors changed over time. The existing theories were evaluated using the conceptual models of the ISPI processes based on the innovationliterature in the IS area. The main focus of the study was to observe changes in the main ISPI processes over time. The main contribution of the thesis is a new theory. The term theory should be understood as 1) a new conceptual framework of the ISPI processes, 2) new ISPI concepts and categories, and the relationships between the ISPI concepts inside the ISPI processes. The study gives a comprehensive and systematic study on the history and evolution of the ISPI processes; reveals the factors that affected ISPI adoption; studies ISPI knowledge acquisition, information transfer, and adaptation mechanisms; and reveals the mechanismsaffecting ISPI unlearning; changes in the ISPI processes; and diverse actors involved in the processes. The results show that both the internal IS department and the two IS software houses sought opportunities to improve their technical skills and career paths and this created an innovative culture. When new technology generations come to the market the platform systems need to be renewed, and therefore the organisations invest in ISPIs in cycles. The extent of internal learning and experiments was higher than the external knowledge acquisition. Until the outsourcing event (1984) the decision-making was centralised and the internalIS department was very influential over ISPIs. After outsourcing, decision-making became distributed between the two IS software houses, the IS client, and itsinternal IT department. The IS client wanted to assure that information systemswould serve the business of the company and thus wanted to co-operate closely with the software organisations.

Predicting diffusion of innovations with self-organisation and machine learning

The main subject of this master's thesis was predicting diffusion of innovations. The prediction was done in a special case: product has been available in some countries, and based on its diffusion in those countries the prediction is done for other countries. The prediction was based on finding similar countries with Self-Organizing Map~(SOM), using parameters of countries. Parameters included various economical and social key figures. SOM was optimised for different products using two different methods: (a) by adding diffusion information of products to the country parameters, and (b) by weighting the country parameters based on their importance for the diffusion of different products. A novel method using Differential Evolution (DE) was developed to solve the latter, highly non-linear optimisation problem. Results were fairly good. The prediction method seems to be on a solid theoretical foundation. The results based on country data were good. Instead, optimisation for different products did not generally offer clear benefit, but in some cases the improvement was clearly noticeable. The weights found for the parameters of the countries with the developed SOM optimisation method were interesting, and most of them could be explained by properties of the products.