A User-Aware and Semantic Approach for Enterprise Search

This article describes how in addition to general purposes search engines, specialized search engines have appeared and have gained their part of the market. An enterprise search engine enables the search inside the enterprise information, mainly web pages but also other kinds of documents; the search is performed by people inside the enterprise or by customers. This article proposes an enterprise search engine called AMBIT-SE that relies on two enhancements: first, it is user-aware in the sense that it takes into consideration the profile of the users that perform the query; second, it exploits semantic techniques to consider not only exact matches but also synonyms and related terms. It performs two main activities: (1) information processing to analyse the documents and build the user profile and (2) search and retrieval to search for information that matches user’s query and profile. An experimental evaluation of the proposed approach is performed on different real websites, showing its benefits over other well-established approaches

Enterprise engineering using semantic technologies

Modern Enterprises are facing unprecedented challenges in every aspect of their businesses: from marketing research, invention of products, prototyping, production, sales to billing. Innovation is the key to enhancing enterprise performances and knowledge is the main driving force in creating innovation. The identification and effective management of valuable knowledge, however, remains an illusive topic. Knowledge management (KM) techniques, such as enterprise process modelling, have long been recognised for their value and practiced as part of normal business. There are plentiful of KM techniques. However, what is still lacking is a holistic KM approach that enables one to fully connect KM efforts with existing business knowledge and practices already in IT systems, such as organisational memories. To address this problem, we present an integrated three-dimensional KM approach that supports innovative semantics technologies. Its automated formal methods allow us to tap into modern business practices and capitalise on existing knowledge. It closes the knowledge management cycle with user feedback loops. Since we are making use of reliable existing knowledge and methods, new knowledge can be extracted with less effort comparing with another method where new information has to be created from scratch

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

Knowledge management support for enterprise distributed systems

Explosion of information and increasing demands on semantic processing web applications have software systems to their limits. To address the problem we propose a semantic based formal framework (ADP) that makes use of promising technologies to enable knowledge generation and retrieval. We argue that this approach is cost effective, as it reuses and builds on existing knowledge and structure. It is also a good starting point for creating an organisational memory and providing knowledge management functions

Web Data Extraction, Applications and Techniques: A Survey

Web Data Extraction is an important problem that has been studied by means of different scientific tools and in a broad range of applications. Many approaches to extracting data from the Web have been designed to solve specific problems and operate in ad-hoc domains. Other approaches, instead, heavily reuse techniques and algorithms developed in the field of Information Extraction. This survey aims at providing a structured and comprehensive overview of the literature in the field of Web Data Extraction. We provided a simple classification framework in which existing Web Data Extraction applications are grouped into two main classes, namely applications at the Enterprise level and at the Social Web level. At the Enterprise level, Web Data Extraction techniques emerge as a key tool to perform data analysis in Business and Competitive Intelligence systems as well as for business process re-engineering. At the Social Web level, Web Data Extraction techniques allow to gather a large amount of structured data continuously generated and disseminated by Web 2.0, Social Media and Online Social Network users and this offers unprecedented opportunities to analyze human behavior at a very large scale. We discuss also the potential of cross-fertilization, i.e., on the possibility of re-using Web Data Extraction techniques originally designed to work in a given domain, in other domains.Comment: Knowledge-based System

Knowledge Management for Public Administrations: Technical Realizations of an Enterprise Attention Management System

The improvement of governments’ efficiency has gained great importance and validity especially in the current times of economic downturn. E-Government constitutes the most contemporary techno-managerial proposition in the track of possible interventions. The paper addresses, more specifically, empowerments necessitated by Public Administration (PA) organizations. Anchored on the needs of three real-life cases, the paper describes the conception and the realization of an IT artefact together with its methodological appeals aiming at improving information access and delivery and thus PAs’ decision making capacity. Our proposition constitutes a novel approach for managing users’ attention in knowledge intensive organizations which goes beyond informing a user about changes in relevant information towards proactively supporting the user to react on changes. The approach is based on an expressive attention model, which is realized by combining ECA (Event-Condition-Action) rules with ontologies. The technical realizations described in the paper constitute the underlying infrastructure of an Enterprise Attention Management System

A survey of QoS-aware web service composition techniques

Web service composition can be briefly described as the process of aggregating services with disparate functionalities into a new composite service in order to meet increasingly complex needs of users. Service composition process has been accurate on dealing with services having disparate functionalities, however, over the years the number of web services in particular that exhibit similar functionalities and varying Quality of Service (QoS) has significantly increased. As such, the problem becomes how to select appropriate web services such that the QoS of the resulting composite service is maximized or, in some cases, minimized. This constitutes an NP-hard problem as it is complicated and difficult to solve. In this paper, a discussion of concepts of web service composition and a holistic review of current service composition techniques proposed in literature is presented. Our review spans several publications in the field that can serve as a road map for future research

Investigating Decision Support Techniques for Automating Cloud Service Selection

The compass of Cloud infrastructure services advances steadily leaving users in the agony of choice. To be able to select the best mix of service offering from an abundance of possibilities, users must consider complex dependencies and heterogeneous sets of criteria. Therefore, we present a PhD thesis proposal on investigating an intelligent decision support system for selecting Cloud based infrastructure services (e.g. storage, network, CPU).Comment: Accepted by IEEE Cloudcom 2012 - PhD consortium trac