Ikram Amous

A user profile modelling using social annotations: a survey

As social networks are growing in terms of the number of users, resources and interactions; the user may be lost or unable to find useful information. Social elements could avoid this disorientation like the social annotations (tags) which become more and more popular and contribute to avoid the disorientation of the user. Representing a user based on these social annotations has showed their utility in reflecting an accurate user profile which could be used for a recommendation purpose. In this paper, we give a state of the art of characteristics of social user and techniques which model and update a tag-based profile. We show how to treat social annotations and the utility of modelling tag-based profiles for recommendation purposes.

A Contribution to Multimedia Document Modeling and Querying

Metadata on multimedia documents may help to describe their content and make their processing easier, for example by identifying events in temporal media, as well as carrying descriptive information for the overall resource. Metadata is essentially static and may be associated with, or embedded in, the multimedia contents. The aim of this paper is to present a proposal for multimedia documents annotation, based on modeling and unifying features elicited from content and structure mining. Our approach relies on the availability of annotated metadata representing segment content and structure as well as segment transcripts. Temporal and spatial operators are also taken into account when annotating documents. Any feature is identified into a descriptor called “meta-document”. These meta-documents are the basis of querying by adapted query languages.

A Contribution to Multimedia Document Modeling and Organizing

This paper presents a solution to resolve the problem of multimedia documents collection reorganizing. This solution is based on a documentary warehouse enriched by metadata (for each media type) elicited, modeled and structured in XML meta-documents. To homogenize these meta-document representation, we based our annotation on a document indexing and segmentation process.The warehouse thus created is seen as the hyperbase to which the user will apply personalization and querying mechanisms. The personalization enables dynamic re-structuring and re-construction of documents answering to the user queries. This approach is based on the OOHDM methodology extension with the use of the metadata.

Social collaborative service recommendation approach based on user’s trust and domain-specific expertise

A few years ago, the Internet of (Web) Service vision came to offer services to all aspects of life and business. The increasing number of Web services make service recommendation a directive research to help users discover services. Furthermore, the rapid development of social network has accelerated the development of social recommendation approach to avoid the data sparsity and cold-start problems that are not treated very well in the collaborative filtering approach. On the one hand, the pervasive use of the social media provides a big social information about the users (e.g., personnel data, social activities, relationships). Hence, the use of trust relation becomes a necessity to filter and select only the useful information. Several trust-aware service recommender systems have been proposed in literature but they do not consider the time in trust level detection among users. On the other hand, in the reality, the majority of users prefer the advice not only of their trusted friends but also their expertise in some domain-specific. In fact, the taking into account of user’ s expertise in recommendation step can resolve the user’ s disorientation problem. For these reasons, we present, in this paper, a Web service decentralized discovery approach which is based on two complementary mechanisms. The trust detection is the first mechanism to detect the social trust level among users. This level is defined in terms of the users’ interactions for a period of time and their interest similarity which are inferred from their social profiles. The service recommendation is the second mechanism which combines the social and collaborative approaches to recommend to the active user the appropriate services according to the expertise level of his most trustworthy friends. This level is extracted from the friends’ past invocation histories according to the domain-specific which is known in advance in the target user’s query. Performance evaluation shows that each proposed mechanism achieves good results. The proposed Level of social Trust (LoT) metric gives better precision more than 50% by comparing with the same metric without taking into account the time factor. The proposed service recommendation mechanism which based on the trust and the domain-specific expertise gives, firstly, a RMSE value lower than other trust-aware recommender systems like TidalTrust, MoleTrust and TrustWalker.Secondly, it provides a better response rate than the recommendation mechanism which based only on trust with a difference equal to 4%.

An Adaptive Method for User Profile Learning

The user profile is a key element in several systems which provide adapted result to the user. Thus, for a better quality of response and to satisfy the user, the profiles content must always be pertinent. So, the removal of irrelevant content is necessary. In this way, we propose in this paper a semi-supervised learning based method for automatically identifying irrelevant profile elements. The originality of this method is that it is based on a new co-training algorithm which is adapted to the content of any profile. For this, our method includes a preparation data step and a classification profile elements process. A comparative evaluation by the classical co-training algorithm shows that our method is better.

AWS-WSDL: a WSDL extension to support adaptive web service

A Web Service is a software component allowing to expose services via Internet. It insures interactions between heterogeneous applications and systems. The explosion of the Internet users number has led to an important diversity of their profiles. Nevertheless, existing Web Services offer the same result regardless the user profile. Therefore, we are interested in defining adaptation solutions that deals with different steps on the service life cycle. In a previous work we were interested in the design step and proposed and detailed an UML (Unified Modeling Language) extension named AWS-UML (Adaptive Web Service Unified Modeling Language) that describes the different allowed users profiles at the metamodel level according to the MDA (Model Driven Architecture) principles and standards. As we modified the design of the Web Service and so the resulting implementation code, we need also to extend the service description in order to support the additional adaptation informations. Thus we introduce in the current paper an extension of the standard WSDL (Web Service Description Language) used to describe the service offered functionalities. Our proposal is named AWS-WSDL (Adaptive Web Service Web Service Description Language).

An Adaptive Navigation Method for Semi-structured Data

The navigation adaptation is the solution that supports the user during his interaction with the system. In the literature, several works that deal with the navigation adaptation are proposed. They guide the user from a document to another, provide the user with a set of links leading to the pertinent documents, or apply on simple links the suitable adaptive navigation technologies. In this paper, we contribute to propose a method that identifies the best navigation path between semi-structured result documents according to the user’s needs, history and device.

SABPEL: Creating self-adaptive business processes

Web services run in complex contexts where arising events may compromise the quality of the whole system. Thus, it is desirable to count on autonomic mechanisms to guide the self-adaptation of service compositions according to changes in the computing infrastructure. In this paper, we propose SABPEL, an extension to the BPEL language allowing dynamic adaptation of composite service. SABPEL include dynamic context and reflection computation. This later allows the service composite to create dynamically adaptable business processes. We use a case study to demonstrate the feasibility and effectiveness of our approach.

ReMoSSA: Reference Model for Specification of Self-adaptive Service-Oriented-Architecture

Specification of SOA has been used to decrease the complexity of service’s development to illustrate the self-adaptive applications. On the one hand, it is a means that provides us the appropriate vocabulary for describing the self-adaptive applications. On the other hand, it grants the key architectural characteristics of self-adaptive service under highly changing environments. In this paper, we present ReMoSSA a formal reference model for specifying self-adaptive Service-Based Applications (SBA). ReMoSSA integrates self-adaptation mechanisms and strategies to provide autonomic and adaptable services. It provides a dynamic monitoring and dynamic adaptation in the design phase. ReMoSSA reduces the cost and the effort of maintenance.

Pertinent User Profile based on Adaptive Semi-supervised Learning

Abstract Several systems such as adaptive systems, etc. provide responses to the user by taking into account, among other, his profile. After each user-system interaction, new information should be added to the user profile content. By the time and after several updating operations, the profile can become overloaded and the removal of irrelevant content is necessary. In this paper, we tackle the profile overloading problem. We propose a new method based on co-training algorithm for detecting and removing irrelevant elements. Our method is automatically adapted to the content of any profile and allows us to obtain the most generic classifier to each one. An experimental study by qualitative and comparative evaluations shows that the proposed method can detect and remove irrelevant profile content effectively.