The privacy dangers of data proliferation on the Web are well-known. Information on the Web has facilitated the deanonymization of anonymous bloggers, the de-sanitization of government records and the identification of individuals based on search engine queries. What has received less attention is Web-mining in support of privacy. In this position paper we argue that the very ability ofWeb data to breach privacy demonstrates its value as a laboratory for the detection of privacy breaches before they happen. In addition, we argue that privacy-invasive services may become privacy-respecting by mining publicly available Web data, with little decrease in performance and efficiency.

Human trafficking is a multi-dimensional problem for which we have incomplete data, limited knowledge of the exploiters, and no understanding of the dynamics of the process. It is a problem that requires a larger, more complete database, understanding of key actors and their interactions in a dynamic environment. These methods exist in the areas of Data Mining, Machine Learning, Network Analysis, and Multi-agent systems. Using these methods, it is possible to create a model which is unique to detecting and preventing human trafficking. These methods can give applicable and successful solutions for different components of the problem of human trafficking. The goal is to build an intelligent system to enable collaboration and analysis, to identify and profile victims, traffickers, buyers, and exploiters, to predict human trafficking patterns, and to disrupt and destabilize human trafficking networks. In this paper, I will outline how some of these methods may be able to help analyze and model the dynamic phenomenon of human trafficking. The purpose is to see whether, using intelligent systems and appropriate collaboration and analysis tools, optimized intervention strategies can be created to profile victims and traffickers as well as impact, dissolve, and disrupt the human trafficking network in such a way that the network is unable to recover.

Some manufacturers provide benchmarks for individual sensors but we found no benchmarks that take a holistic view of the overall screening procedures and no benchmarks that take operator variability into account. Just adding up resources and manpower used is not an effective way for assessing systems where human decision-making and operator compliance to rules play a vital role. Our aim is to develop a decision support tool (cargo-screening system simulator) that will map the right technology and manpower to the right commodity-threat combination in order to maximise detection rates. In this paper we present our ideas for developing such a system and highlight the research challenges we have identified. Then we introduce our first case study and report on the progress we have made so far. Keywords: port security, cargo screening, modelling and simulation, decision support, detection rate matrix 1. INTRODUCTION The primary goal of cargo screening at sea ports and air ports is to detect human stowaways, conventional, nuclear, chemical and radiological weapons and other potential threats. This is an extremely difficult task due to the sheer volume of cargo being moved through ports between countries. For example in sea freight, 200 million containers are moved through 220 ports around the globe every year; this is 90% of all non bulk sea cargo (Dorndorf, Herbers, Panascia, and Zimmermann 2007). Little is known about the efficiency of current cargo screening processes as few benchmarks exist against which they could be measured (e.g.

We introduce supervised latent Dirichlet allocation (sLDA), a statistical model of labelled documents. The model accommodates a variety of response types. We derive an approximate maximum-likelihood procedure for parameter estimation, which relies on variational methods to handle intractable posterior expectations. Prediction problems motivate this research: we use the fitted model to predict response values for new documents. We test sLDA on two real-world problems: movie ratings predicted from reviews, and the political tone of amendments in the U.S. Senate based on the amendment text. We illustrate the benefits of sLDA versus modern regularized regression, as well as versus an unsupervised LDA analysis followed by a separate regression.

Computers understand very little of the meaning of human language. This profoundly limits our ability to give instructions to computers, the ability of computers to explain their actions to us, and the ability of computers to analyse and process text. Vector space models (VSMs) of semantics are beginning to address these limits. This paper surveys the use of VSMs for semantic processing of text. We organize the literature on VSMs according to the structure of the matrix in a VSM. There are currently three broad classes of VSMs, based on term-document, word-context, and pair-pattern matrices, yielding three classes of applications. We survey a broad range of applications in these three categories and we take a detailed look at a specific open source project in each category. Our goal in this survey is to show the breadth of applications of VSMs for semantics, to provide a new perspective on VSMs for those who are already familiar with the area, and to provide pointers into the literature for those who are less familiar with the field.

Internet and expert systems have offered new ways of sharing and distributing knowledge, but there is a lack of researches in the area of web based expert systems. This paper introduces a development of a web-based expert system for the regulations of civil service in the Kingdom of Saudi Arabia named as RCSES. It is the first time to develop such system (application of civil service regulations) as well the development of it using web based approach. The proposed system considers 17 regulations of the civil service system. The different phases of developing the RCSES system are presented, as knowledge acquiring and selection, ontology and knowledge representations using XML format. XML Rule-based knowledge sources and the inference mechanisms were implemented using ASP.net technique. An interactive tool for entering the ontology and knowledge base, and the inferencing was built. It gives the ability to use, modify, update, and extend the existing knowledge base in an easy way. The knowledge was validated by experts in the domain of civil service regulations, and the proposed RCSES was tested, verified, and validated by different technical users and the developers staff. The RCSES system is compared with other related web based expert systems, that comparison proved the goodness, usability, and high performance of RCSES.

The conference Robotics: Science and Systems was held at the Swiss Federal Institute of Technology (ETH) in Zurich Switzerland, from June 25 to June 28, 2008. More than 280 international researchers attended this single track conference to learn about the most exciting robotics research and most advanced robotic systems. The program committee, led by sixteen area chairs, selected 40 papers out of 163 submissions. The program also included seven invited talks and two early career spotlight presentations. The plenary presentations were complemented by thirteen workshops. 

Although AI and HCI explore computing and intelligent behavior and the fields have seen some cross-over, until recently there was not very much. This article outlines a history of the fields that identifies some of the forces that kept the fields at arm’s length. AI was generally marked by a very ambitious, long-term vision requiring expensive systems, although the term was rarely envisioned as being as long as it proved to be, whereas HCI focused more on innovation and improvement of widely-used hardware within a short time-scale. These differences led to different priorities, methods, and assessment approaches.  A consequence was competition for resources, with HCI flourishing in AI winters and moving more slowly when AI was in favor. The situation today is much more promising, in part because of platform convergence: AI can be exploited on widely-used systems.

ICWSM-09 will feature two keynote to education and teaching.

When creating algorithms or systems that are supposed to be used by people, we should be able to adopt a “binocular” view of users’ interaction with intelligent systems: a view that regards the design of interaction and the design of intelligent algorithms as interrelated parts of a single design problem. This special issue offers a coherent set of articles on two levels of generality that illustrate the binocular view and help readers to adopt it.