In this article, we present a novel approach to solving the localization problem in cellular networks. The goal is to estimate a mobile user's position, based on measurements of the signal strengths received from network base stations. Our solution works by building Gaussian process models for the distribution of signal strengths, as obtained in a series of calibration measurements. In the localization stage, the user's position can be estimated by maximizing the likelihood of received signal strengths with respect to the position. We investigate the accuracy of the proposed approach on data obtained within a large indoor cellular network.

Many real-world domains are relational in nature, consisting of a set of objects related to each other in complex ways. This paper focuses on predicting the existence and the type of links between entities in such domains. We apply the relational Markov network framework of Taskar et al. to define a joint probabilistic modelover the entire link graph -- entity attributes and links. The application of the RMN algorithm to this task requires the definition of probabilistic patterns over subgraph structures. We apply this method to two new relational datasets, one involving university webpages, and the other a social network. We show that the collective classification approach of RMNs, and the introduction of subgraph patterns over link labels, provide significant improvements in accuracy over flat classification, which attempts to predict each link in isolation.

We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. We derive upper and lower relative loss bounds for a class of universal learning algorithms involving aswitching dynamics over the choice of the experts. On the basis of the performance bounds we provide the optimal a priori discretization forlearning the parameter that governs the switching dynamics. We demonstrate the new algorithm in the context of wireless networks.

This protocol requires only local communication and simple computations which are distributed among devices.

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, presented the 2004 Spring Symposium Series, Monday through Wednesday, March 22-24, at Stanford University. The titles of the eight symposia were (1) Accessible Hands-on Artificial Intelligence and Robotics Education; (2) Architectures for Modeling Emotion: Cross-Disciplinary Foundations; (3) Bridging the Multiagent and Multirobotic Research Gap; (4) Exploring Attitude and Affect in Text: Theories and Applications; (5) Interaction between Humans and Autonomous Systems over Extended Operation; (6) Knowledge Representation and Ontologies for Autonomous Systems; (7) Language Learning: An Interdisciplinary Perspective; and (8) Semantic Web Services. Most symposia chairs elected to create AAAI technical reports of their symposium, which are available as paperbound reports or (for AAAI members) are downloadable on the AAAI members-only Web site. This report includes summaries of the eight symposia, written by the symposia chairs.

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The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, presented the 2004 Spring Symposium Series, Monday through Wednesday, March 22-24, at Stanford University. The titles of the eight symposia were (1) Accessible Hands-on Artificial Intelligence and Robotics Education; (2) Architectures for Modeling Emotion: Cross-Disciplinary Foundations; (3) Bridging the Multiagent and Multirobotic Research Gap; (4) Exploring Attitude and Affect in Text: Theories and Applications; (5) Interaction between Humans and Autonomous Systems over Extended Operation; (6) Knowledge Representation and Ontologies for Autonomous Systems; (7) Language Learning: An Interdisciplinary Perspective; and (8) Semantic Web Services. Each symposium had limited attendance. Most symposia chairs elected to create AAAI technical reports of their symposium, which are available as paperbound reports or (for AAAI members) are downloadable on the AAAI members-only Web site. This report includes summaries of the eight symposia, written by the symposia chairs.

We have developed a sales-support system for door-to-door sales of cosmetics based on a system called Skin-Expert, a skin-image grading service that includes analysis and diagnosis. Skin-Expert analyzes a customer's current skin quality from a picture of the skin. Several parameters are extracted by image processing, and the skin grading is done by rules generated by data mining from a baseline of grades given by human skin-care experts. Communication with the Skin-Expert is through a cellular telephone with a camera, using e-mail software and a Web browser. Salespeople photograph the customer's skin using the camera in a standard cellular telephone and then send an e-mail message that includes the picture as an attachment to our analysis system. Other parameters associated with the customer (for example, age and gender) are included in the body of the message. The picture is analyzed by our skin-grading system, and the results are made available as a page in HTML format on a customer-accessible Web site. An e-mail is sent when the results are available, usually within minutes. Salespeople check the results by using a Web browser on their cellular telephones. The output not only provides a grading result but also gives recommendations for the care and cosmetics that are most suitable for the customer. Our system integrates cellular communication, Web technology, computer analysis, data mining, and an expert system. Though salespeople use only a cellular telephone with very little computing power as the front end, they can take advantage of intelligent services such as computer grading and data mining. The salespeople do not need to think about what is running in the background, and there is no requirement that end users have any special hardware.

EUROLAN, which has been held biennially since 1993, is one of the most significant European summer schools in the area of natural language processing. Each of the EUROLAN sessions has focused on an area of timely interest to researchers in the field; this year's EUROLAN involved students in tutorials and hands-on sessions concerned with semantic web technologies as applied to language processing, ontology creation and use, and consideration of the semantic web's potential and limitations.

Later in the school, the focus turned to ontologies, which is where the true power of the semantic web lies. EUROLAN lecturers treated its potential in terms of what the topic of ontology development it might--and might not--bring to us in the future. This year's and how great its impact will really start somewhere, somehow, even if school was organized by the Faculty be. Although it is not yet clear what emerges is a variety of ontological of Computer Science at the A. I. Cuza whether the current vision of the semantic stores from which to choose. University of Iasi, the Research Institute web will indeed reach its expectations, The EUROLAN summer school also for Artificial Intelligence at the there are more and more included a workshop on ontologies Romanian Academy in Bucharest, opinions that it represents a major and information extraction, a student and the Department of Computer technological step that will permanently workshop on applied natural Science at Vassar College.