SmartBook – the future E-book and educatonal hypermedia

Доклад по покана, поместен в сборника на Националната конференция "Образованието в информационното общество", Пловдив, май, 2009

Collaborative filtering recommender systems using tag information

Recommender Systems is one of the effective tools to deal with information overload issue. Similar with the explicit rating and other implicit rating behaviours such as purchase behaviour, click streams, and browsing history etc., the tagging information implies user’s important personal interests and preferences information, which can be used to recommend personalized items to users. This paper is to explore how to utilize tagging information to do personalized recommendations. Based on the distinctive three dimensional relationships among users, tags and items, a new user profiling and similarity measure method is proposed. The experiments suggest that the proposed approach is better than the traditional collaborative filtering recommender systems using only rating data.

A reciprocal collaborative method using relevance feedback and feature importance

In a people-to-people matching systems, filtering is widely applied to find the most suitable matches. The results returned are either too many or only a few when the search is generic or specific respectively. The use of a sophisticated recommendation approach becomes necessary. Traditionally, the object of recommendation is the item which is inanimate. In online dating systems, reciprocal recommendation is required to suggest a partner only when the user and the recommended candidate both are satisfied. In this paper, an innovative reciprocal collaborative method is developed based on the idea of similarity and common neighbors, utilizing the information of relevance feedback and feature importance. Extensive experiments are carried out using data gathered from a real online dating service. Compared to benchmarking methods, our results show the proposed method can achieve noticeable better performance.

Client learning and the performance of collaborative infrastructure projects

Australia is a leading user of collaborative procurement methods, which are used to deliver large and complex infrastructure projects. Project alliances, Early Contractor Involvement (ECI), and partnering are typical examples of collaborative procurement models. In order to increase procurement effectiveness and value for money (VfM), clients have adopted various learning strategies for new contract development. However client learning strategies and behaviours have not been systematically analysed before. Therefore, the current paper undertakes a literature review addressing the research question “How can client learning capabilities be effectively understood?”. From the resource-based and dynamic capability perspectives, this paper proposes that the collaborative learning capability (CLC) of clients drives procurement model evolution. Learning routines underpinning CLC carry out exploratory, transformative and exploitative learning phases associated with collaborative project delivery. This learning improves operating routines, and ultimately performance. The conceptualization of CLC and the three sequential learning phases is used to analyse the evidence in the construction management literature. The main contribution of this study is the presentation of a theoretical foundation for future empirical studies to unveil effective learning strategies, which help clients to improve the performance of collaborative projects in the dynamic infrastructure market.

How do construction firms learn on collaborative infrastructure projects?

Construction firms that employ collaborative procurement approaches develop operating routines through joint learning so as to improve infrastructure project performance. This paper reports a study based on a survey sample of 320 construction practitioners which were involved in collaborative infrastructure delivery in Australia. The study developed valid and reliable scales for measuring collaborative learning capability (CLC), and used the scales to evaluate the CLC of contractor and consultant firms within the sample. The evaluation suggests that whilst these firms explore knowledge from both internal and external sources, transform both explicit and tacit knowledge, and apply and internalise new knowledge, they can improve the extent to which these routines are applied to optimise project performance.

incremental learning of triadic plsa for collaborative filtering

Beijing University of Technology (BJUT); Beijing Municipal Lab of Brain Informatics; Chinese Society of Radiology; National Natural Science Foundation of China (NSFC); State Administration of Foreign Experts Affairs

BIWiki - Using a Business Intelligence Wiki to Form a Virtual Community of Practice for Portuguese Master's Students

Web 2.0 software in general and wikis in particular have been receiving growing attention as they constitute new and powerful tools, capable of supporting information sharing, creation of knowledge and a wide range of collaborative processes and learning activities. This paper introduces briefly some of the new opportunities made possible by Web 2.0 or the social Internet, focusing on those offered by the use of wikis as learning spaces. A wiki allows documents to be created, edited and shared on a group basis; it has a very easy and efficient markup language, using a simple Web browser. One of the most important characteristics of wiki technology is the ease with which pages are created and edited. The facility for wiki content to be edited by its users means that its pages and structure form a dynamic entity, in permanent evolution, where users can insert new ideas, supplement previously existing information and correct errors and typos in a document at any time, up to the agreed final version. This paper explores wikis as a collaborative learning and knowledge-building space and its potential for supporting Virtual Communities of Practice (VCoPs). In the academic years (2007/8 and 2008/9), students of the Business Intelligence module at the Master's programme of studies on Knowledge Management and Business Intelligence at Instituto Superior de Estatistica e Gestao de Informacao of the Universidade Nova de Lisboa, Portugal, have been actively involved in the creation of BIWiki - a wiki for Business Intelligence in the Portuguese language. Based on usage patterns and feedback from students participating in this experience, some conclusions are drawn regarding the potential of this technology to support the emergence of VCoPs; some provisional suggestions will be made regarding the use of wikis to support information sharing, knowledge creation and transfer and collaborative learning in Higher Education.

Emotional Intelligence As A Determinant Of Conflict Style Adoption Of Managers: A Theoretical Perspective

Successful management is dependent heavily on the manager’s ability to handle conflict effectively. The workforce has been increasingly becoming diversified vis-à-vis the gender, culture and ethnicity. The present work environment has in itself contributed to sowing seeds of conflict with greater diversity, hostility, complexity and newer business competencies in the work context.The classic study of Mintzberg’s Managerial roles approach (1973) also says that a manager has to spend sufficient time and energy in solving conflict as he has to take roles as a negotiator, and dispute handler. An understanding of the conflict and role that it plays in influencing employee behavior constructively or destructively is immense. Therefore conflict when left unmanaged can lead to diminished cohesiveness amongst employees, productivity and reduced organizational fitness. To manage conflict effective conflict resolution strategies that have constructive outcomes is called for. Conflict resolution style theorists opine that collaborative or integrative style, where there is high concern for task and people is considered to give positive individual and organizational outcomes, while the withdrawing /avoidance style and forcing / dominating style are considered to be ineffective in managing conflict. Though managers have typical preferences in the styles followed it need not necessarily be the typical response as it depends on the context, power relationships, emotions etc. The adoption of conflict styles of managers however is dependent on variables like gender orientation, cultural values, personality orientation, underlying relationships – public/private. The paper attempts to draw the importance of managing conflicts at workplace positively and the need for effective conflict resolution strategies. The conflict style adopted and the variables that affect the adoption of each style are discussed and possible interventions at the workplace are suggested

Collaborative recommender agents based on case-based reasoning and trust

La comunitat científica que treballa en Intel·ligència Artificial (IA) ha dut a terme una gran quantitat de treball en com la IA pot ajudar a les persones a trobar el que volen dins d'Internet. La idea dels sistemes recomanadors ha estat extensament acceptada pels usuaris. La tasca principal d'un sistema recomanador és localitzar ítems, fonts d'informació i persones relacionades amb els interessos i preferències d'una persona o d'un grup de persones. Això comporta la construcció de models d'usuari i l'habilitat d'anticipar i predir les preferències de l'usuari. Aquesta tesi està focalitzada en l'estudi de tècniques d'IA que millorin el rendiment dels sistemes recomanadors. Inicialment, s'ha dut a terme un anàlisis detallat de l'actual estat de l'art en aquest camp. Aquest treball ha estat organitzat en forma de taxonomia on els sistemes recomanadors existents a Internet es classifiquen en 8 dimensions generals. Aquesta taxonomia ens aporta una base de coneixement indispensable pel disseny de la nostra proposta. El raonament basat en casos (CBR) és un paradigma per aprendre i raonar a partir de la experiència adequat per sistemes recomanadors degut als seus fonaments en el raonament humà. Aquesta tesi planteja una nova proposta de CBR aplicat al camp de la recomanació i un mecanisme d'oblit per perfils basats en casos que controla la rellevància i edat de les experiències passades. Els resultats experimentals demostren que aquesta proposta adapta millor els perfils als usuaris i soluciona el problema de la utilitat que pateixen el sistemes basats en CBR. Els sistemes recomanadors milloren espectacularment la qualitat dels resultats quan informació sobre els altres usuaris és utilitzada quan es recomana a un usuari concret. Aquesta tesi proposa l'agentificació dels sistemes recomanadors per tal de treure profit de propietats interessants dels agents com ara la proactivitat, la encapsulació o l'habilitat social. La col·laboració entre agents es realitza a partir del mètode de filtratge basat en la opinió i del mètode col·laboratiu de filtratge a partir de confiança. Els dos mètodes es basen en un model social de confiança que fa que els agents siguin menys vulnerables als altres quan col·laboren. Els resultats experimentals demostren que els agents recomanadors col·laboratius proposats milloren el rendiment del sistema mentre que preserven la privacitat de les dades personals de l'usuari. Finalment, aquesta tesi també proposa un procediment per avaluar sistemes recomanadors que permet la discussió científica dels resultats. Aquesta proposta simula el comportament dels usuaris al llarg del temps basat en perfils d'usuari reals. Esperem que aquesta metodologia d'avaluació contribueixi al progrés d'aquesta àrea de recerca.

Pocket data mining: towards collaborative data mining in mobile computing environments

Pocket Data Mining (PDM) is our new term describing collaborative mining of streaming data in mobile and distributed computing environments. With sheer amounts of data streams are now available for subscription on our smart mobile phones, the potential of using this data for decision making using data stream mining techniques has now been achievable owing to the increasing power of these handheld devices. Wireless communication among these devices using Bluetooth and WiFi technologies has opened the door wide for collaborative mining among the mobile devices within the same range that are running data mining techniques targeting the same application. This paper proposes a new architecture that we have prototyped for realizing the significant applications in this area. We have proposed using mobile software agents in this application for several reasons. Most importantly the autonomic intelligent behaviour of the agent technology has been the driving force for using it in this application. Other efficiency reasons are discussed in details in this paper. Experimental results showing the feasibility of the proposed architecture are presented and discussed.

On-line collaborative learning for in-service teacher education

This article brings some of the results of a study that analyzes a hybrid course for in-service teachers in the Project Teletandem Brazil: foreign languages for all. In this project, Brazilian teachers of Spanish as a foreign language took part in a blended tandem learning course, communicating via videoconferencing with Uruguayan teachers of Portuguese as a foreign language. The aim of the study was to verify Brazilian teachers' concepts and beliefs concerning language and culture and how the teletandem interactions affected them. After the interactions, teachers' views of culture seemed to also incorporate aspects of culture as an interpersonal process, instead of the factual and static view which was previously predominant. Therefore teacher education programs must consider the possibility of conjugating theory and reflective practice through the use of videoconference tools in order to allow teachers to experience culture rather learn facts about it. © 2011 ACADEMY PUBLISHER.