Abstract
Agent technology has been applied in e-commerce to help coping with problems that arise due to its rapid growth. However, despite the amount of research in this area, the level of automation achieved is still limited. This is mainly due to the natural diversity existent in e-commerce environments, where agents may possess different conceptualizations about their needs and capabilities, giving rise to interoperability issues. In this paper we approach this problem and present the AEMOS system as a possible solution. AEMOS is an agent-based e-commerce platform that includes ontology matching services facilitating the interoperability between agents that have different conceptualizations about the same domain of knowledge. The system also explores emergent social networks in order to improve its efficiency by enhancing its ontology matching services and supporting agents in their decisions. © Springer International Publishing Switzerland 2013.

Abstract
In this paper we approach the semantic heterogeneity problem which arises in agent mediated electronic commerce, presenting the AEMOS system as a promising answer. AEMOS is an agent mediated electronic commerce platform which main goal is to enable an efficient and transparent negotiation between agents even when they use different ontologies to represent the same domain of knowledge. The system provides ontology services, more specifically ontology matching services, which are improved by the exploitation of emergent social networks. In this paper we present the currently implemented system and demonstrate how an agent mediated electronic commerce system may benefit from the inclusion and combination of ontology services and social network based support.

Abstract
Publically available text-based documents (e.g. news, meeting transcripts) are a very important source of knowledge, especially for organizations. These documents mention domain entities such as persons, places, professional positions, decisions and actions. Querying these documents (instead of browsing, searching and finding) is a very relevant task for any person in general, and particularly for professionals dealing with intensive knowledge tasks. Querying text-based documents' data, however, is not supported by common technology. For that, such documents' content has to be explicitly and formally captured as facts into a knowledge base. Making use of automatic NLP processes for capturing such facts is a common approach, but their relatively low precision and recall give rise to data quality problems. Furthermore, facts existing in the documents are often insufficient to answer complex queries, thus the need to enrich the captured facts with facts from third-party repositories (e.g. public LOD). This paper describes the adopted process to clean, populate and enrich a knowledge base repository that is further exploited to answer complex queries. This process is triggered by a previous NLP parsing process and conducted by the (rich) ontology describing such repository.

Abstract
AEMOS is a simulator which aims to support the development of agent-based electronic markets capable of dealing with the natural semantic heterogeneity existent in this kind of environment. AEMOS simulates a marketplace which provides ontology matching services, enhanced with the exploitation of emergent social networks, enabling an efficient and transparent communication between agents, even when they use different ontologies. The system recommends possible alignments between the agent's ontologies, and lets them negotiate and decide which alignment should be used to translate the exchanged messages. In this paper we propose a new ontology alignment negotiation process, which promotes the reutilization and combination of already existent alignments, as well as the involvement of the business agents in the alignment composition process. With this new model, we aim to achieve a higher adequacy of the used alignments, as well as a more accurate and trustful evaluation of the alignments. © 2013 DIME UNIVERSITÀ DI GENOVA.

Abstract
Internally agents may use argumentation for both (i) reasoning about what to believe (i.e. theoretical reasoning) and/or (ii) for deciding what to do (i.e. practical reasoning). Despite existing differences between both, from a standpoint of first-personal reflection, a set of considerations for and against a particular conclusion are drawn on both [1]. On the other hand, concerning the types of agents' dialogues (e.g. Deliberation, Negotiation, Persuasion, Inquiry, Information-seeking dialogues), while a clear distinction between each one exist, most of the agents' dialogue occurrences involve mixtures of dialogue types. © Springer-Verlag Berlin Heidelberg 2013.

Abstract
AEMOS is a simulator which aims to support the development of agent-based electronic markets capable of dealing with the natural semantic heterogeneity existent in this kind of environment. AEMOS simulates a marketplace which provides ontology matching services, enhanced with the exploitation of emergent social networks, enabling an efficient and transparent communication between agents, even when they use different ontologies. The system recommends possible alignments between the agents' ontologies, and lets them negotiate and decide which alignment should be used to translate the exchanged messages. In this paper we propose a new ontology alignment negotiation process, which promotes the reutilisation and combination of already existing alignments, as well as the involvement of business agents in the alignment composition process. With this new model, we aim to achieve a higher adequacy of the used alignments, as well as a more accurate and trustful evaluation of the alignments. Copyright © 2015 Inderscience Enterprises Ltd.