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  <title><![CDATA[Enforcing Secure and Robust Routing with Declarative Policies]]></title>
  <description><![CDATA[Internet routers must adhere to many polices gov- erning the selection of paths that meet potentially complex constraints on length, security, symmetry and organizational preferences. Many routing problems are caused by their miscon- figuration, usually due to a combination of human errors and the lack of a high-level formal language for specifying routing policies that can be used to generate router congurations. We describe an approach that obviates many problems by using a declarative lang...]]></description>
  <dc:date>2010-10-31</dc:date>
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  <title><![CDATA[Mapping Web Pages to Database Records via Link Paths]]></title>
  <dc:date>2010-10-26</dc:date>
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  <title><![CDATA[Mining Topic-Level Influence in Heterogeneous Networks]]></title>
  <dc:date>2010-10-26</dc:date>
 </item>
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  <title><![CDATA[SHRINK: A Structural Clustering Algorithm for Detecting Hierarchical Communities in Networks]]></title>
  <dc:date>2010-10-26</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Visual Cube and On-Line Analytical Processing of Images]]></title>
  <dc:date>2010-10-26</dc:date>
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  <title><![CDATA[The Wisdom of Social Multimedia: Using Flickr for Prediction and Forecast]]></title>
  <dc:date>2010-10-25</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[A Policy Based Infrastructure for Social Data Access with Privacy Guarantees]]></title>
  <description><![CDATA[In this paper, we present a policy based infrastructure for social data access with the goal of enabling scientific research, while preservingprivacy. We describe motivating application scenarios that could be enabled with the growing number of user datasets such as social networks, medical datasets etc. These datasets contain sensitive user information and sufficient caution must be exercised while sharing them with third parties to prevent privacy leaks. One of the goals of our framework is...]]></description>
  <dc:date>2010-07-21</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Privacy Preserving Local Asynchronous Algorithm for Feature Selection in a Peer-to-Peer Network]]></title>
  <dc:date>2010-07-20</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Large-Scale Data Mining in Peer-to-peer Networks]]></title>
  <dc:date>2010-07-19</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Semantic Web, Data Mining and Security]]></title>
  <dc:date>2010-07-19</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[I rate you. You rate me. Should we do so publicly?]]></title>
  <description><![CDATA[We find that ratings are not absolute, but rather depend
on whether they are given anonymously or under one’s
own name and whether they are displayed publicly or
held confidentially. The potential to reciprocate produces higher and more correlated ratings than when individuals are unable to see how others rated them. Ratings further depend on the gender and nationalities of the raters and ratees. All of these findings indicate that ratings should not be taken at face value without consid...]]></description>
  <dc:date>2010-06-22</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Classification and Novel Class Detection in Data Streams with Active Mining]]></title>
  <description><![CDATA[We present ActMiner, which addresses four major challenges to data stream classification, namely, infinite length, concept-drift, concept-evolution, and limited labeled data. Most of the existing data stream classification techniques address only the infinite length and concept-drift problems. Our previous work, MineClass, addresses the concept-evolution problem in addition to addressing the infinite length and concept-drift problems. Concept-evolution occurs in the stream when novel classes ...]]></description>
  <dc:date>2010-06-21</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Hierarchical Clustering of Webpages via Cross-Page and In-Page Link Structures]]></title>
  <description><![CDATA[Despite of the wide diversity of web-pages, web-pages re- siding in a particular organization, in most cases, are organized with semantically hierarchic structures. For example, the website of a com- puter science department contains pages about its people, courses and research, among which pages of people are categorized into faculty, staff and students, and pages of research diversify into different areas. Uncov- ering such hierarchic structures could supply users a convenient way of compre...]]></description>
  <dc:date>2010-06-21</dc:date>
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 <item rdf:about="">
  <title><![CDATA[Enforcing Spatial Constraints with Geo-RBAC]]></title>
  <description><![CDATA[Proposed models for spatially-aware extensions of role-based access control (RBAC) combine the administrative and security advantages of RBAC with the dynamic nature of mobile and pervasive computing systems. However, implementing systems that enforce these models poses a number of challenges. As a solution, we propose an architecture for designing such a system. The architecture is based on an enhanced RBAC model that supports location-based access control policies by incorporating spatial c...]]></description>
  <dc:date>2010-06-09</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[The Social Dynamics of Economic Activity in a Virtual World]]></title>
  <description><![CDATA[This paper examines social structures underlying eco- nomic activity in Second Life (SL), a massively multi- player virtual world that allows users to create and trade virtual objects and commodities. We find that users con- duct many of their transactions both within their social networks and within groups. Using frequency of chat as a proxy of tie strength, we observe that free items are more likely to be exchanged as the strength of the tie increases. Social ties particularly play a signif...]]></description>
  <dc:date>2010-05-23</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[EXAM: a comprehensive environment for the analysis of access control policies]]></title>
  <description><![CDATA[Policy integration and inter-operation is often a crucial requirement when parties with different access control policies need to participate in collaborative applications and coalitions. Such requirement is even more difficult to address for dynamic large-scale collaborations, in which the number of access control policies to analyze and compare can be quite large. An important step in policy integration and inter-operation is to analyze the similarity of policies. Policy similarity can some...]]></description>
  <dc:date>2010-05-09</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[CETR Content Extraction via Tag Ratios]]></title>
  <description><![CDATA[We present Content Extraction via Tag Ratios (CETR) – a method to extract content text from diverse webpages by using the HTML document’s tag ratios. We describe how to compute tag ratios on a line-by-line basis and then cluster the resulting histogram into content and non-content areas. Initially, we find that the tag ratio histogram is not easily clustered because of its one-dimensionality; therefore we ex- tend the original approach in order to model the data in two dimensions. Next, w...]]></description>
  <dc:date>2010-04-26</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Topic Initiator Detection on the World Wide Web]]></title>
  <description><![CDATA[In this paper we introduce a new Web mining and search technique - Topic Initiator Detection (TID) on the Web. Given a topic query on the Internet and the resulting col- lection of time-stamped web documents which contain the query keywords, the task of TID is to automatically return which web document (or its author) initiated the topic or was the first to discuss about the topic.
To deal with the TID problem, we design a system frame- work and propose algorithm InitRank (Initiator Ranking)...]]></description>
  <dc:date>2010-04-26</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Controlling Data Disclosure in Computational PIR Protocols]]></title>
  <description><![CDATA[Private Information Retrieval (PIR) protocols allow users to learn data items stored at a server which is not fully trusted, without dis- closing to the server the particular data element retrieved. Several PIR protocols have been proposed, which provide strong guaran- tees on user privacy. Nevertheless, in many application scenarios it is important to protect the database as well. In this paper, we inves- tigate the amount of data disclosed by the the most prominent PIR protocols during a si...]]></description>
  <dc:date>2010-04-13</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Risk-Based Access Control Systems Built of Fuzzy Inferences]]></title>
  <description><![CDATA[Fuzzy inference is a promising approach to implement risk-based access control systems. However, its application to access control raises some novel problems that have not been yet investigated. First, because there are many different fuzzy operations, one must choose the fuzzy operations that best address security requirements. Second, risk-based access control, though it improves information flow and better addresses requirements from critical organizations, may result in damages by malicio...]]></description>
  <dc:date>2010-04-13</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Incentive Compatible Distributed Data Mining]]></title>
  <dc:date>2010-04-01</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Region-based Online Promotion Analysis]]></title>
  <description><![CDATA[This paper addresses a fundamental and challenging problem with broad applications: efficient processing of region-based promotion queries, i.e., to discover the top-k most interesting regions for effective promotion of an object (e.g., a product or a person) given by user, where a region is defined over continuous ranged dimensions. In our problem context, the object can be promoted in a region when it is top-ranked in it. Such type of promotion queries involves an exponentially large search...]]></description>
  <dc:date>2010-03-22</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[A Privacy-Preserving Approach to Policy-Based Content Dissemination]]></title>
  <description><![CDATA[We propose a novel scheme for selective distribution of content, encoded as documents, that preserves the privacy of the users to whom the documents are delivered and is based on an efficient and novel group key management scheme.
Our document broadcasting approach is based on access control policies specifying which users can access which documents, or subdocuments. Based on such policies, a broadcast document is segmented into multiple subdocuments, each encrypted with a different key. In ...]]></description>
  <dc:date>2010-03-01</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Aggregation of Multiple Judgments for Evaluating Ordered Lists]]></title>
  <description><![CDATA[Many tasks (e.g., search and summarization) result in an ordered list of items. In order to evaluate such an ordered list of items, we need to compare it with an ideal ordered list created by a human expert for the same set of items. To reduce any bias, multiple human experts are often used to create multiple ideal ordered lists. An interesting challenge in such an evaluation method is thus how to aggregate these different ideal lists to compute a single score for an ordered list to be evalua...]]></description>
  <dc:date>2010-03-01</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Individual focus and knowledge contribution]]></title>
  <description><![CDATA[Before contributing new knowledge, individuals must attain requisite background knowledge or skills through schooling, training, practice, and experience. Given limited time, individuals often choose either to focus on few areas, where they build deep expertise, or to delve less deeply and distribute their attention and efforts across several areas. In this paper we measure the relationship between the narrowness of focus and the quality of contribution across a range of both traditional and ...]]></description>
  <dc:date>2010-03-01</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Efficient Privacy-Preserving Similar Document Detection]]></title>
  <description><![CDATA[Similar document detection plays important roles in many applications, such as file management, copyright protection, plagiarism prevention, and duplicate submission detection. The state of the art protocols assume that the contents of files stored on a server (or multiple servers) are directly accessible. However, this makes such protocols unsuitable for any environment where the documents themselves are sensitive and cannot be openly read. Essentially, this assumption limits more practical ...]]></description>
  <dc:date>2010-01-16</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Mask: a System for Privacy-Preserving Policy Based Access to Published Content]]></title>
  <description><![CDATA[We propose to demonstrate Mask, the first system addressing the seemingly-unsolvable problem of how to selectively share contents among a group of users based on access control policies expressed as conditions against the identity attributes of these users while at the same time assuring the privacy of these identity attributes from the content publisher. Mask consists of three entities: a Content Publisher, Users referred to as Subscribers, and Identity Providers that issue certified identit...]]></description>
  <dc:date>2010-01-16</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[iTopicModel: Information Network-Integrated Topic Modeling]]></title>
  <description><![CDATA[Document networks, i.e., networks associated with text information, are becoming increasingly popular due to the ubiquity of Web documents, blogs, and various kinds of online data. In this paper, we propose a novel topic modeling framework for document networks, which builds a unified generative topic model that is able to consider both text and structure information for documents. A graphical model is proposed to describe the generative model. On the top layer of this graphical model, we def...]]></description>
  <dc:date>2009-12-06</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[TagLearner: A P2P Classifier Learning System from Collaboratively Tagged Text Documents]]></title>
  <description><![CDATA[The amount of text data on the Internet is growing at a very fast rate. Online text repositories for news agencies, digital libraries and other organizations currently store giga and tera-bytes of data. Large amounts of unstructured text poses a serious challenge for data mining and knowledge extraction. End user participation coupled with distributed computation can play a crucial role in meeting these challenges. In many applications involving classification of text documents, web users oft...]]></description>
  <dc:date>2009-12-06</dc:date>
 </item>
 <item rdf:about="http://www.utdallas.edu/~mxk055100/publications/incentive-trust-assured-info-sharing.pdf">
  <title><![CDATA[Incentive and Trust Issues in Assured Information Sharing]]></title>
  <link>http://www.utdallas.edu/~mxk055100/publications/incentive-trust-assured-info-sharing.pdf</link>
  <description><![CDATA[Assured information sharing among different organizations in a
coalitional environment is an important first step in accomplishing many critical
tasks. For example, different security agencies may need to share intelligence
information for detecting terrorist plots. At the same, each organization
participating in the assured information sharing process may have different
incentives. In this paper, we explore the effects of different incentives and
potential trust issues among organizati...]]></description>
  <dc:date>2009-11-11</dc:date>
 </item>
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