2,320 research outputs found

    Requirements elicitation towards a search engine for semantic multimedia content

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    We investigate user requirements regarding the interface design for a semantic multimedia search and retrieval based on a prototypical implementation of a search engine for multimedia content on the web. Thus, unlike existing image search engines and video search engines, we are interested in true multimedia content combining different media assets into multimedia documents like PowerPoint presentations and Flash files. In a user study with 20 participants, we conducted a formative evaluation based on the think-aloud method and semi-structured interviews in order to obtain requirements to a future web search engine for multimedia content. The interviews are complemented by a paper-and-pencil questionnaire to obtain quantitative information and present mockups demonstrating the user interface of a future multimedia search and retrieval engine

    Knowledge management support for enterprise distributed systems

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    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

    ELICA: An Automated Tool for Dynamic Extraction of Requirements Relevant Information

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    Requirements elicitation requires extensive knowledge and deep understanding of the problem domain where the final system will be situated. However, in many software development projects, analysts are required to elicit the requirements from an unfamiliar domain, which often causes communication barriers between analysts and stakeholders. In this paper, we propose a requirements ELICitation Aid tool (ELICA) to help analysts better understand the target application domain by dynamic extraction and labeling of requirements-relevant knowledge. To extract the relevant terms, we leverage the flexibility and power of Weighted Finite State Transducers (WFSTs) in dynamic modeling of natural language processing tasks. In addition to the information conveyed through text, ELICA captures and processes non-linguistic information about the intention of speakers such as their confidence level, analytical tone, and emotions. The extracted information is made available to the analysts as a set of labeled snippets with highlighted relevant terms which can also be exported as an artifact of the Requirements Engineering (RE) process. The application and usefulness of ELICA are demonstrated through a case study. This study shows how pre-existing relevant information about the application domain and the information captured during an elicitation meeting, such as the conversation and stakeholders' intentions, can be captured and used to support analysts achieving their tasks.Comment: 2018 IEEE 26th International Requirements Engineering Conference Workshop

    ODR, ontologies, and web 2.0

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    Online communities and institutions create new spaces for interaction, but also open new avenues for the emergence of grievances, claims, and disputes. Consequently, online dispute resolution (ODR) procedures are core to these new online worlds. But can ODR mechanisms provide sufficient levels of reputation, trust, and enforceability for it to become mainstream? This contribution introduces the new approaches to ODR and provides a description of the design and structure of Ontomedia, a web-based platform to facilitate online mediation in different domain

    Initiating organizational memories using ontology network analysis

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    One of the important problems in organizational memories is their initial set-up. It is difficult to choose the right information to include in an organizational memory, and the right information is also a prerequisite for maximizing the uptake and relevance of the memory content. To tackle this problem, most developers adopt heavy-weight solutions and rely on a faithful continuous interaction with users to create and improve its content. In this paper, we explore the use of an automatic, light-weight solution, drawn from the underlying ingredients of an organizational memory: ontologies. We have developed an ontology-based network analysis method which we applied to tackle the problem of identifying communities of practice in an organization. We use ontology-based network analysis as a means to provide content automatically for the initial set up of an organizational memory

    Sharing Video Emotional Information in the Web

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    Video growth over the Internet changed the way users search, browse and view video content. Watching movies over the Internet is increasing and becoming a pastime. The possibility of streaming Internet content to TV, advances in video compression techniques and video streaming have turned this recent modality of watching movies easy and doable. Web portals as a worldwide mean of multimedia data access need to have their contents properly classified in order to meet users’ needs and expectations. The authors propose a set of semantic descriptors based on both user physiological signals, captured while watching videos, and on video low-level features extraction. These XML based descriptors contribute to the creation of automatic affective meta-information that will not only enhance a web-based video recommendation system based in emotional information, but also enhance search and retrieval of videos affective content from both users’ personal classifications and content classifications in the context of a web portal.info:eu-repo/semantics/publishedVersio

    The Four Pillars of Crowdsourcing: A Reference Model

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    Crowdsourcing is an emerging business model where tasks are accomplished by the general public; the crowd. Crowdsourcing has been used in a variety of disciplines, including information systems development, marketing and operationalization. It has been shown to be a successful model in recommendation systems, multimedia design and evaluation, database design, and search engine evaluation. Despite the increasing academic and industrial interest in crowdsourcing,there is still a high degree of diversity in the interpretation and the application of the concept. This paper analyses the literature and deduces a taxonomy of crowdsourcing. The taxonomy is meant to represent the different configurations of crowdsourcing in its main four pillars: the crowdsourcer, the crowd, the crowdsourced task and the crowdsourcing platform. Our outcome will help researchers and developers as a reference model to concretely and precisely state their particular interpretation and configuration of crowdsourcing

    prototypical implementations ; working packages in project phase II

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    In this technical report, we present the concepts and first prototypical imple- mentations of innovative tools and methods for personalized and contextualized (multimedia) search, collaborative ontology evolution, ontology evaluation and cost models, and dynamic access and trends in distributed (semantic) knowledge. The concepts and prototypes are based on the state of art analysis and identified requirements in the CSW report IV

    Validation and Evaluation

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    In this technical report, we present prototypical implementations of innovative tools and methods for personalized and contextualized (multimedia) search, collaborative ontology evolution, ontology evaluation and cost models, and dynamic access and trends in distributed (semantic) knowledge, developed according to the working plan outlined in Technical Report TR-B-12-04. The prototypes complete the next milestone on the path to an integral Corporate Semantic Web architecture based on the three pillars Corporate Ontology Engineering, Corporate Semantic Collaboration, and Corporate Semantic Search, as envisioned in TR-B-08-09
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