2,707 research outputs found
Discovery Is Never By Chance: Designing for (Un)Serendipity
Serendipity has a long tradition in the history of science as having played a key role in many significant discoveries. Computer scientists, valuing the role of serendipity in discovery, have attempted to design systems that encourage serendipity. However, that research has focused primarily on only one aspect of serendipity: that of chance encounters. In reality, for serendipity to be valuable chance encounters must be synthesized into insight. In this paper we show, through a formal consideration of serendipity and analysis of how various systems have seized on attributes of interpreting serendipity, that there is a richer space for design to support serendipitous creativity, innovation and discovery than has been tapped to date. We discuss how ideas might be encoded to be shared or discovered by âassociation-huntingâ agents. We propose considering not only the inventorâs role in perceiving serendipity, but also how that inventorâs perception may be enhanced to increase the opportunity for serendipity. We explore the role of environment and how we can better enable serendipitous discoveries to find a home more readily and immediately
Using recommender systems to support idea generation stage
In order to successfully cope with this era of rapid changes, organizations need to develop effective and efficient innovation processes that ensure continuous stream of new valuable ideas that lead to useful innovations. However, generating novel and useful ideas remains a challenging and crucial innovation task. The current paper presents a new use of recommendation systems in the first key activity of the Front End of innovation, and which can assist organizations to improve their ways of generating new ideas. Actually in this paper, we investigate the particular use of recommender systems in the idea generation context to encourage actors to contribute their ideas and ensure the good quality of submitted content. We first present the motivation behind this work and define the concept of recommendation. From this, we deduct the different advantages of using recommender systems in idea generation stage. Next, we provide an overview of existing recommendation approaches. From the literature, we draw a synthesis of important learning gathered. Then, we analyze and discuss based on a set of defined characteristics the use of recommendation systems in this initial phase of idea generation. From the results of this analysis, we formulate a concluding remarks aiming to identify the technique which seems the most suitable to meet our qualitative approach in this specific context.Keywords: idea generation, Recommendation Systems, creativity, collaboration, quality,Innovation
Personality in Computational Advertising: A Benchmark
In the last decade, new ways of shopping online have increased the
possibility of buying products and services more easily and faster
than ever. In this new context, personality is a key determinant
in the decision making of the consumer when shopping. A personâs
buying choices are influenced by psychological factors like
impulsiveness; indeed some consumers may be more susceptible
to making impulse purchases than others. Since affective metadata
are more closely related to the userâs experience than generic
parameters, accurate predictions reveal important aspects of userâs
attitudes, social life, including attitude of others and social identity.
This work proposes a highly innovative research that uses a personality
perspective to determine the unique associations among the
consumerâs buying tendency and advert recommendations. In fact,
the lack of a publicly available benchmark for computational advertising
do not allow both the exploration of this intriguing research
direction and the evaluation of recent algorithms. We present the
ADS Dataset, a publicly available benchmark consisting of 300 real
advertisements (i.e., Rich Media Ads, Image Ads, Text Ads) rated
by 120 unacquainted individuals, enriched with Big-Five usersâ
personality factors and 1,200 personal usersâ pictures
Contextual Social Networking
The thesis centers around the multi-faceted research question of how contexts may
be detected and derived that can be used for new context aware Social Networking
services and for improving the usefulness of existing Social Networking services, giving
rise to the notion of Contextual Social Networking. In a first foundational part,
we characterize the closely related fields of Contextual-, Mobile-, and Decentralized
Social Networking using different methods and focusing on different detailed
aspects. A second part focuses on the question of how short-term and long-term
social contexts as especially interesting forms of context for Social Networking may
be derived. We focus on NLP based methods for the characterization of social relations
as a typical form of long-term social contexts and on Mobile Social Signal
Processing methods for deriving short-term social contexts on the basis of geometry
of interaction and audio. We furthermore investigate, how personal social agents
may combine such social context elements on various levels of abstraction. The third
part discusses new and improved context aware Social Networking service concepts.
We investigate special forms of awareness services, new forms of social information
retrieval, social recommender systems, context aware privacy concepts and services
and platforms supporting Open Innovation and creative processes.
This version of the thesis does not contain the included publications because of
copyrights of the journals etc. Contact in terms of the version with all included
publications: Georg Groh, [email protected] zentrale Gegenstand der vorliegenden Arbeit ist die vielschichtige Frage, wie Kontexte detektiert und abgeleitet werden können, die dazu dienen können, neuartige kontextbewusste Social Networking Dienste zu schaffen und bestehende Dienste in ihrem Nutzwert zu verbessern. Die (noch nicht abgeschlossene) erfolgreiche Umsetzung dieses Programmes fĂŒhrt auf ein Konzept, das man als Contextual Social Networking bezeichnen kann. In einem grundlegenden ersten Teil werden die eng zusammenhĂ€ngenden Gebiete Contextual Social Networking, Mobile Social Networking und Decentralized Social Networking mit verschiedenen Methoden und unter Fokussierung auf verschiedene Detail-Aspekte nĂ€her beleuchtet und in Zusammenhang gesetzt. Ein zweiter Teil behandelt die Frage, wie soziale Kurzzeit- und Langzeit-Kontexte als fĂŒr das Social Networking besonders interessante Formen von Kontext gemessen und abgeleitet werden können. Ein Fokus liegt hierbei auf NLP Methoden zur Charakterisierung sozialer Beziehungen als einer typischen Form von sozialem Langzeit-Kontext. Ein weiterer Schwerpunkt liegt auf Methoden aus dem Mobile Social Signal Processing zur Ableitung sinnvoller sozialer Kurzzeit-Kontexte auf der Basis von Interaktionsgeometrien und Audio-Daten. Es wird ferner untersucht, wie persönliche soziale Agenten Kontext-Elemente verschiedener Abstraktionsgrade miteinander kombinieren können. Der dritte Teil behandelt neuartige und verbesserte Konzepte fĂŒr kontextbewusste Social Networking Dienste. Es werden spezielle Formen von Awareness Diensten, neue Formen von sozialem Information Retrieval, Konzepte fĂŒr kontextbewusstes Privacy Management und Dienste und Plattformen zur UnterstĂŒtzung von Open Innovation und KreativitĂ€t untersucht und vorgestellt. Diese Version der Habilitationsschrift enthĂ€lt die inkludierten Publikationen zurVermeidung von Copyright-Verletzungen auf Seiten der Journals u.a. nicht. Kontakt in Bezug auf die Version mit allen inkludierten Publikationen: Georg Groh, [email protected]
Panorama of Recommender Systems to Support Learning
This chapter presents an analysis of recommender systems in TechnologyEnhanced
Learning along their 15 years existence (2000-2014). All recommender
systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender systems from
35 different countries have been investigated and categorised according to a given
classification framework. The reviewed systems have been classified into 7 clusters
according to their characteristics and analysed for their contribution to the evolution
of the RecSysTEL research field. Current challenges have been identified to lead the work of the forthcoming years.Hendrik Drachsler has been partly supported by the FP7 EU Project LACE (619424).
Katrien Verbert is a post-doctoral fellow of the Research Foundation Flanders
(FWO). Olga C. Santos would like to acknowledge that her contributions to this
work have been carried out within the project Multimodal approaches for Affective
Modelling in Inclusive Personalized Educational scenarios in intelligent Contexts
(MAMIPEC -TIN2011-29221-C03-01). Nikos Manouselis has been partially supported
with funding CIP-PSP Open Discovery Space (297229
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