Towards user profiling for web recommendation

Collaborative recommendation is one of widely used recommendation systems, which recommend items to visitor on a basis of referring other's preference that is similar to current user. User profiling technique upon Web transaction data is able to capture such informative knowledge of user task or interest. With the discovered usage pattern information, it is likely to recommend Web users more preferred content or customize the Web presentation to visitors via collaborative recommendation. In addition, it is helpful to identify the underlying relationships among Web users, items as well as latent tasks during Web mining period. In this paper, we propose a Web recommendation framework based on user profiling technique. In this approach, we employ Probabilistic Latent Semantic Analysis (PLSA) to model the co-occurrence activities and develop a modified k-means clustering algorithm to build user profiles as the representatives of usage patterns. Moreover, the hidden task model is derived by characterizing the meaningful latent factor space. With the discovered user profiles, we then choose the most matched profile, which possesses the closely similar preference to current user and make collaborative recommendation based on the corresponding page weights appeared in the selected user profile. The preliminary experimental results performed on real world data sets show that the proposed approach is capable of making recommendation accurately and efficiently.

Multi-topic information filtering with a single user profile

In Information Filtering (IF) a user may be interested in several topics in parallel. But IF systems have been built on representational models derived from Information Retrieval and Text Categorization, which assume independence between terms. The linearity of these models results in user profiles that can only represent one topic of interest. We present a methodology that takes into account term dependencies to construct a single profile representation for multiple topics, in the form of a hierarchical term network. We also introduce a series of non-linear functions for evaluating documents against the profile. Initial experiments produced positive results.

Computer aided design and analysis of cold formed sections

The work reported in this thesis is concerned with the improvement and expansion of the assistance given to the designer by the computer in the design of cold formed sections. The main contributions have been in four areas, which have consequently led to the fifth, the development of a methodology to optimise designs. This methodology can be considered an `Expert Design System' for cold formed sections. A different method of determining section properties of profiles was introduced, using the properties of line and circular elements. Graphics were introduced to show the outline of the profile on screen. The analysis of beam loading has been expanded to beam loading conditions where the number of supports, point loads, and uniform distributive loads can be specified by the designer. The profile can then be checked for suitability for the specified type of loading. Artificial Intelligence concepts have been introduced to give the designer decision support from the computer, in combination with the computer aided design facilities. The more complex decision support was adopted through the use of production rules. All the support was based on the British standards. A method has been introduced, by which the appropriate use of stiffeners can be determined and consequently designed by the designer. Finally, the methodology by which the designer is given assistance from the computer, without constraining the designer, was developed. This methodology gives advice to the designer on possible methods of improving the design, but allows the designer to reject that option, and analyse the profile accordingly. The methodology enables optimisation to be achieved by the designer, designing variety of profiles for a particular loading, and determining which one is best suited.

Scaling up question-answering to linked data

Linked Data semantic sources, in particular DBpedia, can be used to answer many user queries. PowerAqua is an open multi-ontology Question Answering (QA) system for the Semantic Web (SW). However, the emergence of Linked Data, characterized by its openness, heterogeneity and scale, introduces a new dimension to the Semantic Web scenario, in which exploiting the relevant information to extract answers for Natural Language (NL) user queries is a major challenge. In this paper we discuss the issues and lessons learned from our experience of integrating PowerAqua as a front-end for DBpedia and a subset of Linked Data sources. As such, we go one step beyond the state of the art on end-users interfaces for Linked Data by introducing mapping and fusion techniques needed to translate a user query by means of multiple sources. Our first informal experiments probe whether, in fact, it is feasible to obtain answers to user queries by composing information across semantic sources and Linked Data, even in its current form, where the strength of Linked Data is more a by-product of its size than its quality. We believe our experiences can be extrapolated to a variety of end-user applications that wish to scale, open up, exploit and re-use what possibly is the greatest wealth of data about everything in the history of Artificial Intelligence. © 2010 Springer-Verlag.

Fitness and novelty in evolutionary art

In this paper the effects of introducing novelty search in evolutionary art are explored. Our algorithm combines fitness and novelty metrics to frame image evolution as a multi-objective optimisation problem, promoting the creation of images that are both suitable and diverse. The method is illustrated by using two evolutionary art engines for the evolution of figurative objects and context free design grammars. The results demonstrate the ability of the algorithm to obtain a larger set of fit images compared to traditional fitness-based evolution, regardless of the engine used.

Two Fundamental Problems Connected with AI

This paper is about two fundamental problems in the field of computer science. Solving these two problems is important because it has to do with the creation of Artificial Intelligence. In fact, these two problems are not very famous because they have not many applications outside the field of Artificial Intelligence. In this paper we will give a solution neither of the first nor of the second problem. Our goal will be to formulate these two problems and to give some ideas for their solution.

A Cognitive Science Reasoning in Recognition of Emotions in Audio-Visual Speech

In this report we summarize the state-of-the-art of speech emotion recognition from the signal processing point of view. On the bases of multi-corporal experiments with machine-learning classifiers, the observation is made that existing approaches for supervised machine learning lead to database dependent classifiers which can not be applied for multi-language speech emotion recognition without additional training because they discriminate the emotion classes following the used training language. As there are experimental results showing that Humans can perform language independent categorisation, we made a parallel between machine recognition and the cognitive process and tried to discover the sources of these divergent results. The analysis suggests that the main difference is that the speech perception allows extraction of language independent features although language dependent features are incorporated in all levels of the speech signal and play as a strong discriminative function in human perception. Based on several results in related domains, we have suggested that in addition, the cognitive process of emotion-recognition is based on categorisation, assisted by some hierarchical structure of the emotional categories, existing in the cognitive space of all humans. We propose a strategy for developing language independent machine emotion recognition, related to the identification of language independent speech features and the use of additional information from visual (expression) features.

A WEB-System for Computer Experiments in the Field of Program Transformations

The paper presents basic notions and scientific achievements in the field of program transformations, describes usage of these achievements both in the professional activity (when developing optimizing and unparallelizing compilers) and in the higher education. It also analyzes main problems in this area. The concept of control of program transformation information is introduced in the form of specialized knowledge bank on computer program transformations to support the scientific research, education and professional activity in the field. The tasks that are solved by the knowledge bank are formulated. The paper is intended for experts in the artificial intelligence, optimizing compilation, postgraduates and senior students of corresponding specialties; it may be also interesting for university lecturers and instructors.

Teaching Strategies and Ontologies for E-Learning

* The work is partially suported by Russian Foundation for Basic Studies (grant 02-01-00466).

In memoriam: Dimitar Shishkov

Bulgarian and world computer science lost a prominent colleague: Dimitar Petrov Shishkov 22th January 1939, Varna – 8th March 2004, Sofia D. Shishkov graduated mathematics at Sofia University in 1962. In the last year of his studies he started a specialization as a programmer at the Joint Institute of Nuclear Research – Dubna which lasted three years. Then he worked at the Institute of Mathematics for two years. In 1966 D. Shishkov together with a group of experts transferred to the newly created Central Laboratory for Information Technologies. In 1976 he defended his PhD dissertation. He has been an associate professor in computer science at Sofia University since 1985 and a professor in computer science since 2000. His scientific interests and results were in the fields of computer architectures, computational linguistics, artificial intelligence, numerical methods, data structures, etc. He was remarkable with his teaching activities. D. Shishkov was the creator of high-quality software for the first Bulgarian electronic calculator “ELKA” – one of the first calculators in the world as well as for the series of next calculators and for specialized minicomputers. He was the initiator of the international project “Computerization of the natural languages”. He was a member of a range of international scientific organizations. Among his numerous activities was the organization of the I-st Programming competition in 1979. D. Shishkov was the initiator of sport dancing in Bulgaria (1967) and founder of the first sport-dancing high school education in the world. D. Shishkov was a highly accomplished person with a diversity of interests, with a developed social responsibility and accuracy in his work. In 1996 D. Shishkov was awarded with the International Prize ITHEA for outstanding achievements in the field of Information Theories and Applications. We are grateful to D. Shishkov for the chance to work together with him for establishment and development of IJ ITA.

Intelligent System for Computer Aided Assembly Process Planning

This paper presents the concepts of the intelligent system for aiding of the module assembly technology. The first part of this paper presents a project of intelligent support system for computer aided assembly process planning. The second part includes a coincidence description of the chosen aspects of implementation of this intelligent system using technologies of artificial intelligence (artificial neural networks, fuzzy logic, expert systems and genetic algorithms).