45,643 research outputs found
PlanetOnto: from news publishing to integrated knowledge management support
Given a scenario in which members of an academic community collaboratively construct and share an archive of news items, several knowledge management challenges arise. The authors' integrated suite of tools, called PlanetOnto, supports a speedy but high quality publishing process, allows ontology-driven document formalization and augments standard browsing and search facilities with deductive knowledge retrieva
Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques
Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to
be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning
methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories.
We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that
proposes a new form of interaction between users and digital libraries, where the latter are adapted to users
and their surroundings
Designing Interfaces to Support Collaboration in Information Retrieval
Information retrieval systems should acknowledge the existence of collaboration in the search process. Collaboration can help users to be more effective in both learning systems and in using them. We consider some issues of viewing interfaces to information retrieval systems as collaborative notations and how to build systems that more actively support collaboration. We describe a system that embodies just one kind of explicit support; a graphical representation of the search process that can be manipulated and discussed by the users. By acknowledging the importance of other people in the search process, we can develop systems that not only improve help-giving by people but which can lead to a more robust search activity, more able to cope with, and indeed exploit, the failures of any intelligent agents used
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
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