Personalized web search using clickthrough data and web page rating

Personalization of Web search is to carry out retrieval for each user incorporating his/her interests. We propose a novel technique to construct personalized information retrieval model from the users' clickthrough data and Web page ratings. This model builds on the userbased collaborative filtering technology and the top-N resource recommending algorithm, which consists of three parts: user profile, user-based collaborative filtering, and the personalized search model. Firstly, we conduct user's preference score to construct the user profile from clicked sequence score and Web page rating. Then it attains similar users with a given user by user-based collaborative filtering algorithm and calculates the recommendable Web page scoring value. Finally, personalized informaion retrieval be modeled by three case applies (rating information for the user himself; at least rating information by similar users; not make use of any rating information). Experimental results indicate that our technique significantly improves the search performance. © 2012 ACADEMY PUBLISHER

Metrics for ranking ontologies

Representing knowledge using domain ontologies has shown to be a useful mechanism and format for managing and exchanging information. Due to the difficulty and cost of building ontologies, a number of ontology libraries and search engines are coming to existence to facilitate reusing such knowledge structures. The need for ontology ranking techniques is becoming crucial as the number of ontologies available for reuse is continuing to grow. In this paper we present AKTiveRank, a prototype system for ranking ontologies based on the analysis of their structures. We describe the metrics used in the ranking system and present an experiment on ranking ontologies returned by a popular search engine for an example query

Source control SUDS delivery on a global scale and in Scotland including approach by responsible organisations and professional groups

Background to researchThe Sustainable Urban Drainage Scottish Working Party via CREW commissioned this work on the implementation of source control for SUDS in Scotland. The project is being carried out by researchers based at Abertay University Dundee involves three phases. These are presented in separate reports; this report covers phase 2 of that work. Source control sustainable urban drainage systems (SUDS) are an established technique in many parts of the world. Source control SUDS are a key component of what is termed the stormwater treatment train. Source controls manage the more frequent but smaller polluting rainfall events as close to the source as possible (where the rain falls). Site and regional control SUDS are larger downstream structures which manage the longer term rainfall events and provide additional treatment when required. One of the key advantages of managing the more frequent rainfall events at source is that downstream site and regional SUDS will have longer life spans resulting in overall cost efficiencies. Scotland is regarded as a frontrunner in the UK regarding implementation of SUDS with site and regional drainage structures now considered ‘business as usual’. However the uptake of source control is less routine than would be expected.Objectives of researchPhase one of this research looked at the background to the evolution of source control in Scotland to provide an insight into the enabling factors and obstacles for uptake of the systems since. Phase two(this report) appraises delivery of the systems in seven countries and case studies are developed to understand why source control was implemented and how it was achieved. The current delivery by responsible organisations and professional groups which encourage and influence the source control agenda in Scotland is also appraised. Using these findings, the transition pathway from traditional drainage to source control SUDS are reconstructed and mapped out to highlight the historical and current enabling (and disabling) factors to realise the transition to date. A transition framework is used to highlight the transition strengths developed by responsible organisations over the last two decades which had assisted in accelerating the transition.Key findings and recommendationsKey outcomes of this research include:* In Scotland the source control vision and agenda is fragmented due to different stakeholder drivers and funding mechanisms.* There are examples of the use of incentives in Scotland (i.e. legislative, regulatory, financial,social and environmental) to drive integrated agendas. However these have not been successfully showcased to provide the evidence base for encouraging replication and up-scaling of the methodologies and techniques.* There are limited frontier source control SUDS ‘niches’ to nurture innovative techniques such as raingardens – a learning by doing concept. A more focused research agenda to validate these systems as viable sustainable solutions for Scotland would assist in accelerating uptake.* Lack of sector engagement, particularly with the public is a disabling factor for uptake.A final observation from this phase of the study is that requests from various interested parties for CREW / SUDS Working Party to share outputs indicates the need for this research

Link-based similarity search to fight web spam

www.ilab.sztaki.hu/websearch We investigate the usability of similarity search in fighting Web spam based on the assumption that an unknown spam page is more similar to certain known spam pages than to honest pages. In order to be successful, search engine spam never appears in isolation: we observe link farms and alliances for the sole purpose of search engine ranking manipulation. The artificial nature and strong inside connectedness however gave rise to successful algorithms to identify search engine spam. One example is trust and distrust propagation, an idea originating in recommender systems and P2P networks, that yields spam classificators by spreading information along hyperlinks from white and blacklists. While most previous results use PageRank variants for propagation, we form classifiers by investigating similarity top lists of an unknown page along various measures such as co-citation, companion, nearest neighbors in low dimensional projections and SimRank. We test our method over two data sets previously used to measure spam filtering algorithms. 1

The Requirements for Ontologies in Medical Data Integration: A Case Study

Evidence-based medicine is critically dependent on three sources of information: a medical knowledge base, the patients medical record and knowledge of available resources, including where appropriate, clinical protocols. Patient data is often scattered in a variety of databases and may, in a distributed model, be held across several disparate repositories. Consequently addressing the needs of an evidence-based medicine community presents issues of biomedical data integration, clinical interpretation and knowledge management. This paper outlines how the Health-e-Child project has approached the challenge of requirements specification for (bio-) medical data integration, from the level of cellular data, through disease to that of patient and population. The approach is illuminated through the requirements elicitation and analysis of Juvenile Idiopathic Arthritis (JIA), one of three diseases being studied in the EC-funded Health-e-Child project.Comment: 6 pages, 1 figure. Presented at the 11th International Database Engineering & Applications Symposium (Ideas2007). Banff, Canada September 200

Ontology selection: ontology evaluation on the real Semantic Web

The increasing number of ontologies on the Web and the appearance of large scale ontology repositories has brought the topic of ontology selection in the focus of the semantic web research agenda. Our view is that ontology evaluation is core to ontology selection and that, because ontology selection is performed in an open Web environment, it brings new challenges to ontology evaluation. Unfortunately, current research regards ontology selection and evaluation as two separate topics. Our goal in this paper is to explore how these two tasks relate. In particular, we are interested to get a better understanding of the ontology selection task and filter out the challenges that it brings to ontology evaluation. We discuss requirements posed by the open Web environment on ontology selection, we overview existing work on selection and point out future directions. Our major conclusion is that, even if selection methods still need further development, they have already brought novel approaches to ontology evaluatio