Anupam Joshi

An ontology for context-aware pervasive computing environments

This document describes COBRA-ONT, an ontology for supporting pervasive context-aware systems. COBRA-ONT, expressed in the Web Ontology Language OWL, is a collection of ontologies for describing places, agents and events and their associated properties in an intelligent meeting-room domain. This ontology is developed as a part of the Context Broker Architecture (CoBrA), a broker-centric agent architecture that provides knowledge sharing, context reasoning and privacy protection supports for pervasive context-aware systems. We also describe an inference engine for reasoning with information expressed using the COBRA-ONT ontology and the ongoing research in using the DAML-Time ontology for context reasoning.

Swoogle: a search and metadata engine for the semantic web

Swoogle is a crawler-based indexing and retrieval system for the Semantic Web. It extracts metadata for each discovered document, and computes relations between documents. Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents. One of the interesting properties we compute is <i>ontology rank</i>, a measure of the importance of a Semantic Web document.

SOUPA: standard ontology for ubiquitous and pervasive applications

We describe a shared ontology called SOUPA - standard ontology for ubiquitous and pervasive applications. SOUPA is designed to model and support pervasive computing applications. This ontology is expressed using the Web ontology language OWL and includes modular component vocabularies to represent intelligent agents with associated beliefs, desires, and intentions, time, space, events, user profiles, actions, and policies for security and privacy. We discuss how SOUPA can be extended and used to support the applications of CoBrA, a broker-centric agent architecture for building smart meeting rooms, and MoGATU, a peer-to-peer data management for pervasive environments.

A policy language for a pervasive computing environment

We describe a policy language designed for pervasive computing applications that is based on deontic concepts and grounded in a semantic language. The pervasive computing environments under consideration are those in which people and devices are mobile and use various wireless networking technologies to discover and access services and devices in their vicinity. Such pervasive environments lend themselves to policy-based security due to their extremely dynamic nature. Using policies allows the security functionality to be modified without changing the implementation of the entities involved. However, along with being extremely dynamic, these environments also tend to span several domains and be made up of entities of varied capabilities. A policy language for environments of this sort needs to be very expressive but lightweight and easily extensible. We demonstrate the feasibility of our policy language in pervasive environments through a prototype used as part of a secure pervasive system.

Social networks applied

Social networks have interesting properties. They influence our lives enormously without us being aware of the implications they raise. The authors investigate the following areas concerning social networks: how to exploit our unprecedented wealth of data and how we can mine social networks for purposes such as marketing campaigns; social networks as a particular form of influence, i.e.., the way that people agree on terminology and this phenomenons implications for the way we build ontologies and the Semantic Web; social networks as something we can discover from data; the use of social network information to offer a wealth of new applications such as better recommendations for restaurants, trustworthy email senders, or (maybe) blind dates; investigation of the richness and difficulty of harvesting FOAF (friend-of-a-friend) information; and by looking at how information processing is bound to social context, the resulting ways that network topologys definition determines its outcomes.

Low-complexity fuzzy relational clustering algorithms for Web mining

This paper presents new algorithms-fuzzy c-medoids (FCMdd) and robust fuzzy c-medoids (RFCMdd)-for fuzzy clustering of relational data. The objective functions are based on selecting c representative objects (medoids) from the data set in such a way that the total fuzzy dissimilarity within each cluster is minimized. A comparison of FCMdd with the well-known relational fuzzy c-means algorithm (RFCM) shows that FCMdd is more efficient. We present several applications of these algorithms to Web mining, including Web document clustering, snippet clustering, and Web access log analysis.

A policy based approach to security for the semantic web

Along with developing specifications for the description of meta-data and the extraction of information for the Semantic Web, it is important to maximize security in this environment, which is fundamentally dynamic, open and devoid of many of the clues human societies have relied on for security assessment. Our research investigates the marking up of web entities with a semantic policy language and the use of distributed policy management as an alternative to traditional authentication and access control schemes. The policy language allows policies to be described in terms of deontic concepts and models speech acts, which allows the dynamic modification of existing policies, decentralized security control and less exhaustive policies. We present a security framework, based on this policy language, which addresses security issues for web resources, agents and services in the Semantic Web.

Semantic Web in the context broker architecture

This document describes a new architecture that exploits semantic Web technologies for supporting pervasive context-aware systems. This architecture called context broker architecture (CobrA) differs from other architectures in using the Web ontology language OWL for modelling ontologies of context and for supporting context reasoning. Central to our architecture is a broker agent that maintains a shared model of context for all computing entities in the space and enforces the privacy policies defined by the users when sharing their contextual information. We describe the use of CoBrA, its associated ontologies, and its privacy protection mechanism in an intelligent meeting room prototype.

Intelligent agents meet the semantic Web in smart spaces

A new smart meeting room system called EasyMeeting explores the use of multi-agent systems, Semantic Web ontologies, reasoning, and declarative policies for security and privacy. Building on an earlier pervasive computing system, EasyMeeting provides relevant services and information to meeting participants based on their situational needs. The system also exploits the context-aware support provided by the Context Broker Architecture (Cobra). Cobras intelligent broker agent maintains a shared context model for all computing entities in the space and enforces user-defined privacy policies.

Toward Distributed service discovery in pervasive computing environments

The paper proposes a novel distributed service discovery protocol for pervasive environments. The protocol is based on the concepts of peer-to-peer caching of service advertisements and group-based intelligent forwarding of service requests. It does not require a service to be registered with a registry or lookup server. Services are described using the Web Ontology Language (OWL). We exploit the semantic class/subClass hierarchy of OWL to describe service groups and use this semantic information to selectively forward service requests. OWL-based service description also enables increased flexibility in service matching. We present simulation results that show that our protocol achieves increased efficiency in discovering services (compared to traditional broadcast-based mechanisms) by efficiently utilizing bandwidth via controlled forwarding of service requests.