3,440 research outputs found
The other side of the social web: A taxonomy for social information access
The power of the modern Web, which is frequently called the Social Web or Web 2.0, is frequently traced to the power of users as contributors of various kinds of contents through Wikis, blogs, and resource sharing sites. However, the community power impacts not only the production of Web content, but also the access to all kinds of Web content. A number of research groups worldwide explore what we call social information access techniques that help users get to the right information using "collective wisdom" distilled from actions of those who worked with this information earlier. This invited talk offers a brief introduction into this important research stream and reviews recent works on social information access performed at the University of Pittsburgh's PAWS Lab lead by the author. Copyright © 2012 by the Association for Computing Machinery, Inc. (ACM)
Adaptive Information Visualization for Personalized Access to Educational Digital Libraries
Personalization is one of the emerging ways to increase the power of modern Digital Libraries. The Knowledge Sea II system presented in this paper explores social navigation support, an approach for providing personalized guidance within the open corpus of educational resources. Following the concepts of social navigation we have attempted to organize a personalized navigation support that is based on past learners’ interaction with the system. The study indicates that Knowledge Sea II became the students' primary tool for accessing the open corpus documents used in a programming course. The social navigation support implemented in this system was considered useful by students participating in the study of Knowledge Sea II. At the same time, some user comments indicated the need to provide more powerful navigational support, such as the ability to rank the usefulness of a page
Current Challenges and Visions in Music Recommender Systems Research
Music recommender systems (MRS) have experienced a boom in recent years,
thanks to the emergence and success of online streaming services, which
nowadays make available almost all music in the world at the user's fingertip.
While today's MRS considerably help users to find interesting music in these
huge catalogs, MRS research is still facing substantial challenges. In
particular when it comes to build, incorporate, and evaluate recommendation
strategies that integrate information beyond simple user--item interactions or
content-based descriptors, but dig deep into the very essence of listener
needs, preferences, and intentions, MRS research becomes a big endeavor and
related publications quite sparse.
The purpose of this trends and survey article is twofold. We first identify
and shed light on what we believe are the most pressing challenges MRS research
is facing, from both academic and industry perspectives. We review the state of
the art towards solving these challenges and discuss its limitations. Second,
we detail possible future directions and visions we contemplate for the further
evolution of the field. The article should therefore serve two purposes: giving
the interested reader an overview of current challenges in MRS research and
providing guidance for young researchers by identifying interesting, yet
under-researched, directions in the field
A Personalized System for Conversational Recommendations
Searching for and making decisions about information is becoming increasingly
difficult as the amount of information and number of choices increases.
Recommendation systems help users find items of interest of a particular type,
such as movies or restaurants, but are still somewhat awkward to use. Our
solution is to take advantage of the complementary strengths of personalized
recommendation systems and dialogue systems, creating personalized aides. We
present a system -- the Adaptive Place Advisor -- that treats item selection as
an interactive, conversational process, with the program inquiring about item
attributes and the user responding. Individual, long-term user preferences are
unobtrusively obtained in the course of normal recommendation dialogues and
used to direct future conversations with the same user. We present a novel user
model that influences both item search and the questions asked during a
conversation. We demonstrate the effectiveness of our system in significantly
reducing the time and number of interactions required to find a satisfactory
item, as compared to a control group of users interacting with a non-adaptive
version of the system
What Europe Knows and Thinks About Algorithms Results of a Representative Survey. Bertelsmann Stiftung eupinions February 2019
We live in an algorithmic world. Day by day, each of us is affected by decisions that algorithms make for and about
us – generally without us being aware of or consciously perceiving this. Personalized advertisements in social
media, the invitation to a job interview, the assessment of our creditworthiness – in all these cases, algorithms
already play a significant role – and their importance is growing, day by day.
The algorithmic revolution in our daily lives undoubtedly brings with it great opportunities. Algorithms are masters
at handling complexity. They can manage huge amounts of data quickly and efficiently, processing it consistently
every time. Where humans reach their cognitive limits, find themselves making decisions influenced by the day’s
events or feelings, or let themselves be influenced by existing prejudices, algorithmic systems can be used to
benefit society. For example, according to a study by the Expert Council of German Foundations on Integration and
Migration, automotive mechatronic engineers with Turkish names must submit about 50 percent more applications
than candidates with German names before being invited to an in-person job interview (Schneider, Yemane and
Weinmann 2014). If an algorithm were to make this decision, such discrimination could be prevented. However,
automated decisions also carry significant risks: Algorithms can reproduce existing societal discrimination and
reinforce social inequality, for example, if computers, using historical data as a basis, identify the male gender as
a labor-market success factor, and thus systematically discard job applications from woman, as recently took place
at Amazon (Nickel 2018)
An E-Book Building Methodology Using An Extensible Personalization Structure For Operationalizing E-Book Interface Metaphors
In order to address these
problems, this thesis aims to identify requirements of personalization elements, to
represent e-book personalization, to formalize e-book personalization components, and
to develope-book packaging control and standards.Untuk menangani masalah-masalah ini, tesis ini bertujuan mengenal pasti keperluan
elemen pemperibadian, untuk memperwakilkan pemperibadian e-book, untuk
memformalkan komponen pemperibadian e-book, dan membangunkan pakej kawalan
dan piawaian e-book
Information Outlook, July 2001
Volume 5, Issue 7https://scholarworks.sjsu.edu/sla_io_2001/1006/thumbnail.jp
Design of interactive visualization of models and students data
This document reports the design of the interactive visualizations of open student models that will
be performed in GRAPPLE. The visualizations will be based on data stored in the domain model and student model, and aim at supporting learners to be more engaged in the learning process, and instructors in assisting the learners
Ec(h)o: Situated play in a tangible and audio museum guide
In this paper we discuss an adaptive museum guide prototype in which playfulness is a key design goal for the interaction experience. The interface for our prototype is a combined tangible user interface and audio display. We discuss how we determined the specific requirements for play through an ethnographic study and analysis based on ecological concepts of Bell and Nardi & O’Day. We found that we could consider play in two main forms in regard to the interface: content and physical play. We also found that play is highly contextual. Designers need to consider the situated nature of play for two reasons: 1) to best serve the overall design purpose; 2) in order to understand the nature and degree of play required. We augmented traditional user experience evaluation methods of questionnaires and interviews with observational analysis based on Djajadiningrat’s descriptions of aesthetic interaction
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