2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology

This paper deals with large scale information retrieval aiming at contributing to web searching. The collections of documents considered are huge and not obvious to tackle with classical approaches. The greater the number of documents belonging to the collection, the more powerful approach required. A Bees Swarm Optimization algorithm called BSO-IR is designed to explore the prohibitive number of ... View full abstract»

The target of many studies in the health sciences is the discovery of cause-effect relationships among observed variables of interest, for example: treatments, exposures, preconditions, and outcomes. Causal modeling and causal discovery are central to medical science. In order to algorithmically consider causal relations, the relations must be placed into a representation that supports manipulatio... View full abstract»

Representing meaning is a major challenge facing Web 3.0. However, it is extremely difficult to excavate the meaning of a target concept from textual data as there is no one-to-one correspondence between the textual unit in which the target concept is embedded and the conceptual content that we would like to excavate. In this paper, we propose one possible approach for addressing this challenge, b... View full abstract»

This paper focuses on heuristics retrieval in human problem solvingby combining computational cognitive modeling and neuro imaging. An event-related fMRI (functional Magnetic Resonance Imaging) experiment was conducted on a simplified Sudoku puzzle problem solving and an ACT-R (Adaptive Control of Thought-Rational) cognitive model was developed to simulate the information processing processes of h... View full abstract»

A biologically inspired cognitive model is presented for human decision making and applied to the simulation of the web user. The model is based on the Neurophysiology description of multiple decision process; this is a well proven psychological theory. The model simulates the behaviour of a real user on a website and it was observed that the distribution of artificial web users in sessions succes... View full abstract»

Expertise matching, aiming to find the alignment between experts and queries, is a common problem in many real applications such as conference paper-reviewer assignment, product-reviewer alignment, and product-endorser matching. Most of existing methods for this problem usually find “relevant” experts for each query independently by using, e.g., an information retrieval method. However, in real-wo... View full abstract»

Automated end-to-end Service Level Management (SLM) is crucial to enable self-organising Service-Oriented Architectures (SOA). In this paper, we present an approach based on Organic Computing to enable automated SLM by using automated service level negotiation. The evaluation results in a simulated SOA environment are presented to show the applicability of our approach. View full abstract»

Data management and analysis has become an integral component in the area of reservoir engineering. An important metric that determines the overall effectiveness of data analysis is data quality. Data provenance, the metadata that pertains to the derivation history of data objects, has emerged as an invaluable asset in evaluating data quality. The reservoir facilities and software systems that col... View full abstract»

Search engines have greatly influenced the way people access information on the Internet as such engines provide the preferred entry point to billions of pages on the Web. Therefore, highly ranked web pages generally have higher visibility to people and pushing the ranking higher has become the top priority for webmasters. As a matter of fact, search engine optimization (SEO) has became a sizeable... View full abstract»

We propose using multi-layer multiple instance learning (MMIL) for image set classification and applying it to the task of cannabis website classification. We treat each image as an instance in an image set, then each image is further viewed as containing instances of local image patches. This representation naturally extends traditional multiple instance learning (MIL) to multi-layers. We then sh... View full abstract»

Expert Collaborative Filtering is an approach to recommender systems in which recommendations for users are derived from ratings coming from domain experts rather than peers. In this paper we present an implementation of this approach in the music domain. We show the applicability of the model in this setting, and show how it addresses many of the shortcomings in traditional Collaborative Filterin... View full abstract»