An Online Framework for Supporting the Evaluation of Personalised Information Retrieval Systems

Scope - Personalised Information Retrieval (PIR) has been gaining attention because it investigates intelligent ways for enhancing content delivery. Web users can have personalised services and more accurate information. Problem - Several PIR systems have been proposed in the literature; however, they have not been properly tested or evaluated. Proposal – The authors propose a generally applicable web-based interface, which provides PIR developers and evaluators with: i) implicit recommendations on how to evaluate a specific PIR system; ii) a repository containing studies on user-centred and layered evaluation studies; iii) recommendations on how to best combine different evaluation methods, metrics and measurement criteria in order to most effectively evaluate their system; iv) a UCE methodology which details how to apply existing UCE techniques; v) a taxonomy of evaluations of adaptive systems; and vi) interface translation support (49 languages supported)

Web Page Recommendation System using Self Organizing Map Technique

The exponential explosion of various contents on the Web, made Recommendation Systems increasingly indispensable. Innumerable different kinds of recommendations are made on the Web every day, including movies, music, images, books recommendations, query suggestions and tags recommendations, etc. The paper aims to provide the users with most relevant results (URL’s) to the respective query word. The developed System uses the K-means technique and the Modified System uses the Self-Organizing Map technique. Both the methods use historical browsers data for search key words and provide users with most relevant web pages. All users click-through activity such as number of times he visited, duration he spent, and several other variables are stored in database. The Systems use this database and process to cluster and rank them. The results obtained shows that the Self Organizing Map technique produce most relevant results for a particular query word compared to K-means technique. The Self Organizing Map technique is the optimal method for Web Page recommendations. The Modified System can be utilized in many recommendation tasks on the World Wide Web, including expert finding, image recommendations, image annotations, etc. The experimental results show the promising future of our work

Boosting Cross-Language Retrieval by Learning Bilingual Phrase Associations from Relevance Rankings

We present an approach to learning bilingual n-gram correspondences from relevance rankings of English documents for Japanese queries. We show that directly optimizing cross-lingual rankings rivals and complements machine translation-based cross-language information retrieval (CLIR). We propose an efficient boosting algorithm that deals with very large cross-product spaces of word correspondences. We show in an experimental evaluation on patent prior art search that our approach, and in particular a consensus-based combination of boosting and translation-based approaches, yields substantial improvements in CLIR performance. Our training and test data are made publicly available.

A WEB PERSONALIZATION ARTIFACT FOR UTILITY-SENSITIVE REVIEW ANALYSIS

Online customer reviews are web content voluntarily posted by the users of a product (e.g. camera) or service (e.g. hotel) to express their opinions about the product or service. Online reviews are important resources for businesses and consumers. This dissertation focuses on the important consumer concern of review utility, i.e., the helpfulness or usefulness of online reviews to inform consumer purchase decisions. Review utility concerns consumers since not all online reviews are useful or helpful. And, the quantity of the online reviews of a product/service tends to be very large. Manual assessment of review utility is not only time consuming but also information overloading. To address this issue, review helpfulness research (RHR) has become a very active research stream dedicated to study utility-sensitive review analysis (USRA) techniques for automating review utility assessment. Unfortunately, prior RHR solution is inadequate. RHR researchers call for more suitable USRA approaches. Our current research responds to this urgent call by addressing the research problem: What is an adequate USRA approach? We address this problem by offering novel Design Science (DS) artifacts for personalized USRA (PUSRA). Our proposed solution extends not only RHR research but also web personalization research (WPR), which studies web-based solutions for personalized web provision. We have evaluated the proposed solution by applying three evaluation methods: analytical, descriptive, and experimental. The evaluations corroborate the practical efficacy of our proposed solution. This research contributes what we believe (1) the first DS artifacts to the knowledge body of RHR and WPR, and (2) the first PUSRA contribution to USRA practice. Moreover, we consider our evaluations of the proposed solution the first comprehensive assessment of USRA solutions. In addition, this research contributes to the advancement of decision support research and practice. The proposed solution is a web-based decision support artifact with the capability to substantially improve accurate personalized webpage provision. Also, website designers can apply our research solution to transform their works fundamentally. Such transformation can add substantial value to businesses

CLIR teknikak baliabide urriko hizkuntzetarako

152 p.Hizkuntza arteko informazioaren berreskurapenerako sistema bat garatxean kontsulta itzultzea da hizkuntzaren mugari aurre egiteko hurbilpenik erabiliena. Kontsulta itzultzeko estrategia arrakastatsuenak itzulpen automatikoko sistem aedo corpus paraleloetan oinarritzen dira, baina baliabide hauek urriak dira baliabide urriko hizkuntzen eszenatokietan. Horrelako egoeretan egokiagoa litzateke eskuragarriago diren baliabideetan oinarritutako komtsulta itzultzeko estrategia bat. Tesi honetan frogatu nahi dugu baliabide nagusi horiek hiztegi elebiduna eta horren osagarri diren corpus konparagarriak eta kontsulta-saioak izan daitezkeela. // Hizkuntza arteko informazioaren berreskurapenerako sistema bat garatxean kontsulta itzultzea da hizkuntzaren mugari aurre egiteko hurbilpenik erabiliena. Kontsulta itzultzeko estrategia arrakastatsuenak itzulpen automatikoko sistem aedo corpus paraleloetan oinarritzen dira, baina baliabide hauek urriak dira baliabide urriko hizkuntzen eszenatokietan. Horrelako egoeretan egokiagoa litzateke eskuragarriago diren baliabideetan oinarritutako komtsulta itzultzeko estrategia bat. Tesi honetan frogatu nahi dugu baliabide nagusi horiek hiztegi elebiduna eta horren osagarri diren corpus konparagarriak eta kontsulta-saioak izan daitezkeela