SmartWeb: Mobile Access to the Semantic Web

Ankolekar A, Cimiano P, Hitzler P, et al. SmartWeb: Mobile Access to the Semantic Web. In: Wache H, ed. Proceedings of the ESWC2006 poster and demo session. 2006: 3-4

Supporting Online Problem Solving Communities with the Semantic Web

The Web plays a critical role in hosting Web communities, their content and interactions. A prime example is the open source software (OSS) community, whose members, including software developers and users, interact almost exclusively over the Web, constantly generating, sharing and refining content in the form of software code through active interaction over the Web on code design and bug resolution processes. The Semantic Web is an envisaged extension of the current Web, in which content is given a welldefined meaning, through the specification of metadata and ontologies, increasing the utility of the content and enabling information from heterogeneous sources to be integrated. We developed a prototype Semantic Web system for OSS communities, Dhruv. Dhruv provides an enhanced semantic interface to bug resolution messages and recommends related software objects and artifacts. Dhruv uses an integrated model of the OpenACS community, the software, and the Web interactions, which is semi-automatically populated from the existing artifacts of the community

A Semantic Future for AI

In our modern information society, people need to manage ever-increasing numbers of personal devices and conduct more of their work and activities online, often making use of heterogeneous services. The amount of information to be processed by each individual is constantly growing, making it increasingly difficult to control, channel, share and make constructive use of it. To mitigate this, computing needs to become much more human-centered, e.g. by presenting personalised information to users and by respecting personal preferences in controlling multiple devices or invoking various services. Appropriate representation of the semantics of the information and functionality of devices and services will be critical to such personalised computing. Symbolic artificial intelligence (AI) techniques provide the method of choice for the required semantic representation and reasoning capabilities. The challenge for symbolic AI is to be able to support large-scale, distributed, dynamic knowledge bases enabling highly adaptive and evolving systems. AI must also look to specific application contexts and develop real-world solutions for problems in those domains. Below, we present some examples of such application contexts

Rules for an Ontology-based Approach to Adaptation

Tran DT, Cimiano P, Ankolekar A. Rules for an Ontology-based Approach to Adaptation. In: Proceedings of the 1st International Workshop on Semantic Media Adaptation and Personalization. 2006

A Rule-based Adaption Model for Ontology-based Personalization

Tran DT, Cimiano P, Ankolekar A. A Rule-based Adaption Model for Ontology-based Personalization. In: Wallace M, Angelides M, Mylonas P, eds. Advances in Semantic Media Adaptation and Personalization. Studies in Computational Intelligence; 93. Berlin, Heidelberg: Springer; 2008: 117-135.Various adaptive hypermedia systems have been proposed to alleviate information overload on the Web by personalising the delivery of information and resources to the user. These systems have however been afflicted with difficulties in the acquisition of an accurate user model, a limited degree of customization offered to the user as well as general lack of user control on and transparency of the systems’ adaptive behavior. In this chapter, we argue that the use of rules on top on ontologies can enable adaptive functionality that is transparent and controllable for users. To this end, we present ODAS, a domain ontology for adaptive hypermedia systems, and a model for the specification of ODAS-based adaptation rules. We demonstrate the use of this model by showing how it can be instantiated within a knowledge portal to arrive at rules that exploit ODAS semantics to perform meaningful personalization