14,611 research outputs found
A Model of User Preferences for Semantic Services Discovery and Ranking
Current proposals on Semantic Web Services discovery and
ranking are based on user preferences descriptions that often come with
insufficient expressiveness, consequently making more difficult or even
preventing the description of complex user desires. There is a lack of a
general and comprehensive preference model, so discovery and ranking
proposals have to provide ad hoc preference descriptions whose expressiveness
depends on the facilities provided by the corresponding technique,
resulting in user preferences that are tightly coupled with the
underlying formalism being used by each concrete solution. In order to
overcome these problems, in this paper an abstract and sufficiently expressive
model for defining preferences is presented, so that they may be
described in an intuitively and user-friendly manner. The proposed model
is based on a well-known query preference model from database systems,
which provides highly expressive constructors to describe and compose
user preferences semantically. Furthermore, the presented proposal is independent
from the concrete discovery and ranking engines selected, and
may be used to extend current Semantic Web Service frameworks, such
as wsmo, sawsdl, or owl-s. In this paper, the presented model is also
validated against a complex discovery and ranking scenario, and a concrete
implementation of the model in wsmo is outlined.Comisión Interministerial de Ciencia y Tecnología TIN2006-00472Comisión Interministerial de Ciencia y Tecnología TIN2009-07366Junta de Andalucía TIC-253
Semantic web service automation with lightweight annotations
Web services, both RESTful and WSDL-based, are an increasingly important part of the Web. With the application of semantic technologies, we can achieve automation of the use of those services. In this paper, we present WSMO-Lite and MicroWSMO, two related lightweight approaches to semantic Web service description, evolved from the WSMO framework. WSMO-Lite uses SAWSDL to annotate WSDL-based services, whereas MicroWSMO uses the hRESTS microformat to annotate RESTful APIs and services. Both frameworks share an ontology for service semantics together with most of automation algorithms
Discovering the Impact of Knowledge in Recommender Systems: A Comparative Study
Recommender systems engage user profiles and appropriate filtering techniques
to assist users in finding more relevant information over the large volume of
information. User profiles play an important role in the success of
recommendation process since they model and represent the actual user needs.
However, a comprehensive literature review of recommender systems has
demonstrated no concrete study on the role and impact of knowledge in user
profiling and filtering approache. In this paper, we review the most prominent
recommender systems in the literature and examine the impression of knowledge
extracted from different sources. We then come up with this finding that
semantic information from the user context has substantial impact on the
performance of knowledge based recommender systems. Finally, some new clues for
improvement the knowledge-based profiles have been proposed.Comment: 14 pages, 3 tables; International Journal of Computer Science &
Engineering Survey (IJCSES) Vol.2, No.3, August 201
Semantic-driven matchmaking of web services using case-based reasoning
With the rapid proliferation of Web services as the medium of choice to securely publish application services beyond the firewall, the importance of accurate, yet flexible matchmaking of similar services gains importance both for the human user and for dynamic composition engines. In this paper, we present a novel approach that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and matchmaking. Our framework considers Web services execution experiences in the decision making process and is highly adaptable to the service requester constraints. The framework also utilises OWL semantic descriptions extensively for implementing both the components of the CBR engine and the matchmaking profile of the Web services
Social Search with Missing Data: Which Ranking Algorithm?
Online social networking tools are extremely popular, but can miss potential discoveries latent in the social 'fabric'. Matchmaking services which can do naive profile matching with old database technology are too brittle in the absence of key data, and even modern ontological markup, though powerful, can be onerous at data-input time. In this paper, we present a system called BuddyFinder which can automatically identify buddies who can best match a user's search requirements specified in a term-based query, even in the absence of stored user-profiles. We deploy and compare five statistical measures, namely, our own CORDER, mutual information (MI), phi-squared, improved MI and Z score, and two TF/IDF based baseline methods to find online users who best match the search requirements based on 'inferred profiles' of these users in the form of scavenged web pages. These measures identify statistically significant relationships between online users and a term-based query. Our user evaluation on two groups of users shows that BuddyFinder can find users highly relevant to search queries, and that CORDER achieved the best average ranking correlations among all seven algorithms and improved the performance of both baseline methods
Defining and Prototyping a Life-cycle for Dynamic Service Composition
Since the Internet has become a commodity in both wired and wireless environments, new applications and paradigms have emerged to explore this highly distributed and widespread system. One such paradigm is service-orientation, which enables the provision of software functionality as services, \ud
allowing in this way the construction of distributed systems with loosely coupled parts. The Service-Oriented Architecture (SOA) provides a set of principles to create service-oriented systems, by defining how services can be \ud
created, composed, published, discovered and invoked. In accordance with these principles, in this paper we address the challenge of performing dynamic service composition. The composition process and its associated tasks have to be precisely defined so that the different problems of dynamic service composition can be identified and tackled. To achieve this, this paper defines a life-cycle for dynamic service composition, which defines the required phases and stakeholders. Furthermore, we present our prototype in which the different phases of the dynamic service composition life-cycle are being implemented. This prototype is being used to experiment with and validate our initial ideas on dynamic service composition
Sensor Search Techniques for Sensing as a Service Architecture for The Internet of Things
The Internet of Things (IoT) is part of the Internet of the future and will
comprise billions of intelligent communicating "things" or Internet Connected
Objects (ICO) which will have sensing, actuating, and data processing
capabilities. Each ICO will have one or more embedded sensors that will capture
potentially enormous amounts of data. The sensors and related data streams can
be clustered physically or virtually, which raises the challenge of searching
and selecting the right sensors for a query in an efficient and effective way.
This paper proposes a context-aware sensor search, selection and ranking model,
called CASSARAM, to address the challenge of efficiently selecting a subset of
relevant sensors out of a large set of sensors with similar functionality and
capabilities. CASSARAM takes into account user preferences and considers a
broad range of sensor characteristics, such as reliability, accuracy, location,
battery life, and many more. The paper highlights the importance of sensor
search, selection and ranking for the IoT, identifies important characteristics
of both sensors and data capture processes, and discusses how semantic and
quantitative reasoning can be combined together. This work also addresses
challenges such as efficient distributed sensor search and
relational-expression based filtering. CASSARAM testing and performance
evaluation results are presented and discussed.Comment: IEEE sensors Journal, 2013. arXiv admin note: text overlap with
arXiv:1303.244
Personalizable Service Discovery in Pervasive Systems
Today, telecom providers are facing changing challenges.
To stay ahead in the competition and provide market
leading offerings, carriers need to enable a global ecosystem of
third party independent application developers to deliver converged
services. This is the aim of leveraging a open standardsbased
service delivery platform. To identify and to cope with
those challenges is the main target of the EU funded project
IST DAIDALOS II. And a central point to satisfy the changing
user needs is the provision of a well working, user friendly and
personalized service discovery. This paper describes our work
in the project on a middleware in a framework for pervasive
service usage. We have designed an architecture for it, that
enables full transparency to the user, grants high compatibility
and extendability by a modular and pluggable conception and
allows for interoperability with most known service discovery
protocols. Our Multi-Protocol Service Discovery and the Four
Phases Service Filtering concept enabling personalization should
allow for the best possible results in service discovery
Non-functional Property based service selection: A survey and classification of approaches
In recent years there has been much effort dedicated to developing approaches for service selection based on non-functional properties. It is clear that much progress has been made, and by considering the individual approaches there is some overlap in functionality, but obviously also some divergence. In this paper we contribute a classification of approaches, that is, we define a number of criteria which allow to differentiate approaches. We use this classification to provide a comparison of existing approaches and in that sense provide a survey of the state of the art of the field. Finally we make some suggestions as to where the research in this area might be heading and which new challenges need to be addressed
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