2,292 research outputs found
CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap
After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in
multimedia search engines, we have identified and analyzed gaps within European research effort during our second year.
In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio-
economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown
of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on
requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the
community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our
Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as
National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core
technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research
challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal
challenges
Proceedings of the 3rd Workshop on Social Information Retrieval for Technology-Enhanced Learning
Learning and teaching resource are available on the Web - both in terms of digital learning content and people resources (e.g. other learners, experts, tutors). They can be used to facilitate teaching and learning tasks. The remaining challenge is to develop, deploy and evaluate Social information retrieval (SIR) methods, techniques and systems that provide learners and teachers with guidance in potentially overwhelming variety of choices. The aim of the SIRTEL’09 workshop is to look onward beyond recent achievements to discuss specific topics, emerging research issues, new trends and endeavors in SIR for TEL. The workshop will bring together researchers and practitioners to present, and more importantly, to discuss the current status of research in SIR and TEL and its implications for science and teaching
Information search and similarity based on Web 2.0 and semantic technologies
The World Wide Web provides a huge amount of information described in natural language at the current society’s disposal. Web search engines were born from the necessity of finding a particular piece of that information. Their ease of use and their utility have turned these engines into one of the most used web tools at a daily basis. To make a query, users just have to introduce a set of words - keywords - in natural language and the engine answers with a list of ordered resources which contain those words. The order is given by
ranking algorithms. These algorithms use basically two types of features: dynamic and
static factors. The dynamic factor has into account the query; that is, those documents
which contain the keywords used to describe the query are more relevant for that query.
The hyperlinks structure among documents is an example of a static factor of most current
algorithms. For example, if most documents link to a particular document, this document
may have more relevance than others because it is more popular.
Even though currently there is a wide consensus on the good results that the majority of
web search engines provides, these tools still suffer from some limitations, basically 1) the
loneliness of the searching activity itself; and 2) the simple recovery process, based mainly
on offering the documents that contains the exact terms used to describe the query.
Considering the first problem, there is no doubt in the lonely and time-consuming process
of searching relevant information in the World Wide Web. There are thousands of users out
there that repeat previously executed queries, spending time in taking decisions of which
documents are relevant or not; decisions that may have been taken previously and that
may be do the job for similar or identical queries for other users.
Considering the second problem, the textual nature of the current Web makes the
reasoning capability of web search engines quite restricted; queries and web resources are
described in natural language that, in some cases, can lead to ambiguity or other semantic-related
difficulties. Computers do not know text; however, if semantics is incorporated to the text, meaning and sense is incorporated too. This way, queries and web resources will
not be mere sets of terms, but lists of well-defined concepts.
This thesis proposes a semantic layer, known as Itaca, which joins simplicity and
effectiveness in order to endow with semantics both the resources stored in the World Wide
Web and the queries used by users to find those resources. This is achieved through
collaborative annotations and relevance feedback made by the users themselves, which
describe both the queries and the web resources by means of Wikipedia concepts.
Itaca extends the functional capabilities of current web search engines, providing a new
ranking algorithm without dispensing traditional ranking models. Experiments show that this
new architecture offers more precision in the final results obtained, keeping the simplicity
and usability of the web search engines existing so far. Its particular design as a layer
makes feasible its inclusion to current engines in a simple way.Internet pone a disposiciĂłn de la sociedad una enorme cantidad de informaciĂłn descrita en
lenguaje natural. Los buscadores web nacieron de la necesidad de encontrar un fragmento
de informaciĂłn entre tanto volumen de datos. Su facilidad de manejo y su utilidad los han
convertido en herramientas de uso diario entre la poblaciĂłn. Para realizar una consulta, el
usuario sĂłlo tiene que introducir varias palabras clave en lenguaje natural y el buscador
responde con una lista de recursos que contienen dichas palabras, ordenados en base a
algoritmos de ranking. Estos algoritmos usan dos tipos de factores básicos: factores
dinámicos y estáticos. El factor dinámico tiene en cuenta la consulta en sĂ; es decir,
aquellos documentos donde estén las palabras utilizadas para describir la consulta serán
más relevantes para dicha consulta. La estructura de hiperenlaces en los documentos
electrónicos es un ejemplo de factor estático. Por ejemplo, si muchos documentos enlazan
a otro documento, éste último documento podrá ser más relevante que otros.
Si bien es cierto que actualmente hay consenso entre los buenos resultados de estos
buscadores, todavĂa adolecen de ciertos problemas, destacando 1) la soledad en la que un
usuario realiza una consulta; y 2) el modelo simple de recuperaciĂłn, basado en ver si un
documento contiene o no las palabras exactas usadas para describir la consulta.
Con respecto al primer problema, no hay duda de que navegar en busca de cierta
información relevante es una práctica solitaria y que consume mucho tiempo. Hay miles de
usuarios ahĂ fuera que repiten sin saberlo una misma consulta, y las decisiones que toman
muchos de ellos, descartando la información irrelevante y quedándose con la que
realmente es Ăştil, podrĂan servir de guĂa para otros muchos.
Con respecto al segundo, el carácter textual de la Web actual hace que la capacidad de
razonamiento en los buscadores se vea limitada, pues las consultas y los recursos están
descritos en lenguaje natural que en ocasiones da origen a la ambigĂĽedad. Los equipos
informáticos no comprenden el texto que se incluye. Si se incorpora semántica al lenguaje, se incorpora significado, de forma que las consultas y los recursos electrónicos no son
meros conjuntos de términos, sino una lista de conceptos claramente diferenciados.
La presente tesis desarrolla una capa semántica, Itaca, que dota de significado tanto a los
recursos almacenados en la Web como a las consultas que pueden formular los usuarios
para encontrar dichos recursos. Todo ello se consigue a través de anotaciones
colaborativas y de relevancia realizadas por los propios usuarios, que describen tanto
consultas como recursos electrĂłnicos mediante conceptos extraĂdos de Wikipedia. Itaca
extiende las caracterĂsticas funcionales de los buscadores web actuales, aportando un
nuevo modelo de ranking sin tener que prescindir de los modelos actualmente en uso. Los
experimentos demuestran que aporta una mayor precisiĂłn en los resultados finales,
manteniendo la simplicidad y usabilidad de los buscadores que se conocen hasta ahora.
Su particular diseño, a modo de capa, hace que su incorporación a buscadores ya
existentes sea posible y sencilla.Programa Oficial de Posgrado en IngenierĂa TelemáticaPresidente: AsunciĂłn GĂłmez PĂ©rez.- Secretario: Mario Muñoz Organero.- Vocal: Anselmo Peñas Padill
CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines
Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective.
The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines.
From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research
From the knowledge acquisition bottleneck to the knowledge acquisition overflow: A brief French history of knowledge acquisition
International audienceThis article is an account of the evolution of the French-speaking research community on knowledge acquisition and knowledge modelling echoing the complex and cross-disciplinary trajectory of the field. In particular, it reports the most significant steps in the parallel evolution of the web and the knowledge acquisition paradigm, which finally converged with the project of a semantic web. As a consequence of the huge amount of available data in the web, a paradigm shift occurred in the domain, from knowledge-intensive problem solving to large-scale data acquisition and management. We also pay a tribute to Rose Dieng, one of the pioneers of this research community
Exploiting the conceptual space in hybrid recommender systems: a semantic-based approach
Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, octubre de 200
EzWeb/FAST: Reporting on a Successful Mashup-based Solution for Developing and Deploying Composite Applications in the Upcoming Web of Services
Service oriented architectures (SOAs) based on Web Services have attracted a great interest and IT investments during the last years, principally in the context of business-to-business integration within corporate intranets. However, they are nowadays evolving to break through enterprise boundaries, in a revolutionary attempt to make the approach pervasive, leading to what we call a user-centric SOA, i.e. a SOA conceived as a Web of Services made up of compositional resources that empowers end-users to ubiquitously exploit these resources by collaboratively remixing them. In this paper we explore the architectural basis, technologies, frameworks and tools considered necessary to face this novel vision of SOA. We also present the rationale behind EzWeb/FAST: an undergoing EU funded project whose first outcomes could serve as a preliminary proof of concep
Social Search: retrieving information in Online Social Platforms -- A Survey
Social Search research deals with studying methodologies exploiting social
information to better satisfy user information needs in Online Social Media
while simplifying the search effort and consequently reducing the time spent
and the computational resources utilized. Starting from previous studies, in
this work, we analyze the current state of the art of the Social Search area,
proposing a new taxonomy and highlighting current limitations and open research
directions. We divide the Social Search area into three subcategories, where
the social aspect plays a pivotal role: Social Question&Answering, Social
Content Search, and Social Collaborative Search. For each subcategory, we
present the key concepts and selected representative approaches in the
literature in greater detail. We found that, up to now, a large body of studies
model users' preferences and their relations by simply combining social
features made available by social platforms. It paves the way for significant
research to exploit more structured information about users' social profiles
and behaviors (as they can be inferred from data available on social platforms)
to optimize their information needs further
state of the art analysis ; working packages in project phase II
In this report, we introduce our goals and present our requirement analysis
for the second phase of the Corporate Semantic Web project. Corporate ontology
engineering will improve the facilitation of agile ontology engineering to
lessen the costs of ontology development and, especially, maintenance.
Corporate semantic collaboration focuses the human-centered aspects of
knowledge management in corporate contexts. Corporate semantic search is
settled on the highest application level of the three research areas and at
that point it is a representative for applications working on and with the
appropriately represented and delivered background knowledge
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