Personalised Query Suggestion for Intranet Search with Temporal User Profiling

Recent research has shown the usefulness of using collective user interaction data (e.g., query logs) to recommend query modification suggestions for Intranet search. However, most of the query suggestion approaches for Intranet search follow an ``one size fits all'' strategy, whereby different users who submit an identical query would get the same query suggestion list. This is problematic, as even with the same query, different users may have different topics of interest, which may change over time in response to the user's interaction with the system. In this paper, we address the problem by proposing a personalised query suggestion framework for Intranet search. For each search session, we construct two temporal user profiles: a click user profile using the user's clicked documents and a query user profile using the user's submitted queries. We then use the two profiles to re-rank the non-personalised query suggestion list returned by a state-of-the-art query suggestion method for Intranet search. Experimental results on a large-scale query logs collection show that our personalised framework significantly improves the quality of suggested queries

Dynamic User Profiling for Search Personalisation

The performance of a personalised search system largely depends upon the ability to build user profiles which accurately capture the user's search interests. However, many approaches to user profiling have neglected the dynamic nature of the user's search interests. That is, a user's search interests typically change in response to their interactions with the search system during the search period. Therefore, a profile built for previous searches might not reflect that user's current search interests. A widely used type of profile represents the topical interests of the user. In these cases, a typical approach is to build a user profile using topics discussed in documents which the user has found relevant, and where the topics are obtained from a human-generated ontology or directory. However, a key limitation of these approaches is that many documents may not contain the topics covered in the ontology. Moreover, the human-generated ontology requires manual effort to determine the correct categories for each document. In this research, we address these problems by proposing novel techniques for dynamically building user profiles which capture the user's search interests changing over time. Instead of using a human-generated ontology, we use a topic modelling technique (Latent Dirichlet Allocation) for unsupervised extraction of the topics from documents. To dynamically build user profiles, we make two important assumptions. First, that the group of users with whom a user shares a set of common interests may be different depending upon the particular topic of interest. Second, the more recently clicked/relevant documents tell us more about the user's current search interests. To test these assumptions, we develop and implement dynamic user profiles, and then evaluate them on two search personalisation tasks. Our first chosen task is personalising search results returned by a Web search engine, and the second is the task of personalising query suggestions made by an Intranet search engine. We found that dynamic user profiles can significantly improve the ranking quality over well-established baselines

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Fuzzy rule based profiling approach for enterprise information seeking and retrieval

With the exponential growth of information available on the Internet and various organisational intranets there is a need for profile based information seeking and retrieval (IS&R) systems. These systems should be able to support users with their context-aware information needs. This paper presents a new approach for enterprise IS&R systems using fuzzy logic to develop task, user and document profiles to model user information seeking behaviour. Relevance feedback was captured from real users engaged in IS&R tasks. The feedback was used to develop a linear regression model for predicting document relevancy based on implicit relevance indicators. Fuzzy relevance profiles were created using Term Frequency and Inverse Document Frequency (TF/IDF) analysis for the successful user queries. Fuzzy rule based summarisation was used to integrate the three profiles into a unified index reflecting the semantic weight of the query terms related to the task, user and document. The unified index was used to select the most relevant documents and experts related to the query topic. The overall performance of the system was evaluated based on standard precision and recall metrics which show significant improvements in retrieving relevant documents in response to user queries

Search engine Performance optimization: methods and techniques [version 3; peer review: 2 approved, 1 not approved]

Background With the rapid advancement of information technology, search engine optimisation (SEO) has become crucial for enhancing the visibility and relevance of online content. In this context, the use of cloud platforms like Microsoft Azure is being explored to bolster SEO capabilities. Methods This scientific article offers an in-depth study of search engine optimisation. It explores the different methods and techniques used to improve the performance and efficiency of a search engine, focusing on key aspects such as result relevance, search speed and user experience. The article also presents case studies and concrete examples to illustrate the practical application of optimisation techniques. Results The results demonstrate the importance of optimisation in delivering high quality search results and meeting the increasing demands of users. Conclusions The article addresses the enhancement of search engines through the Microsoft Azure infrastructure and its associated components. It highlights methods such as indexing, semantic analysis, parallel searches, and caching to strengthen the relevance of results, speed up searches, and optimise the user experience. Following the application of these methods, a marked improvement was observed in these areas, thereby showcasing the capability of Microsoft Azure in enhancing search engines. The study sheds light on the implementation and analysis of these Azure-focused techniques, introduces a methodology for assessing their efficacy, and details the specific benefits of each method. Looking forward, the article suggests integrating artificial intelligence to elevate the relevance of results, venturing into other cloud infrastructures to boost performance, and evaluating these methods in specific scenarios, such as multimedia information search. In summary, with Microsoft Azure, the enhancement of search engines appears promising, with increased relevance and a heightened user experience in a rapidly evolving sector

Revitalising executive information systems for supporting executive intelligence activities

A thesis submitted for the degree of Doctor of Philosophy of the Univeristy of BedfordshireWith the increasing amount, complexity and dynamism of operational and strategic information in electronic and distributed environment, executives are seeking assistance for continuous, self-reactive and self-adaptive activities or approaches of acquiring, synthesising and interpreting information for intelligence with a view to determining the course of action - executive intelligence activities. Executives Information Systems (EIS) were originally emerged as a computer-based tool to help senior executives to manage the search and process of information. EIS was popularised in 1990's but EIS study have not advanced to a great extent in either research or practice since its prevalence in the mid and late 1990's. Conventional EIS studies have established some views and guidelines for EIS design and development, but the guidelines underpinned by preceding research have failed to develop robust yet rational EIS for handling the current executive's information environment. The most common deficiency of traditional EIS is the static and inflexible function with predetermined information needs and processes designed for static performance monitoring and control. The current emergence of the intelligent software agent, as a concept and a technology, with applications, provides prospects and advanced solutions for supporting executive's information processing activities in a more integrated and distributed environment of the Internet. Although software agents offer the prospective to support information processing activities intelligently, executive's desires and perception of agent-based support must be elucidated in order to develop a system that is considered valuable for executives. This research attempts to identify executive criteria of an agent-based EIS for supporting executive intelligence activities. Firstly, four focus groups were conducted to explore and reveal the current state of executive's information environment and information processing behaviour in the light of Internet era, from which to examine the validity of the conventional views of EIS purpose, functions and design guidelines. Initial executive criteria for agent-based EIS design were also identified in the focus group study. Secondly, 25 senior managers were interviewed for deeper insights on value-added attributes and processes of executive criteria for building agent-based EIS. The findings suggest a "usability-adaptability-intelligence" trichotomy of agent-based EIS design model that comprises executive criteria of value-added attributes and processes for building a usable, adaptable and intelligent EIS

JISC Preservation of Web Resources (PoWR) Handbook

Handbook of Web Preservation produced by the JISC-PoWR project which ran from April to November 2008. The handbook specifically addresses digital preservation issues that are relevant to the UK HE/FE web management community”. The project was undertaken jointly by UKOLN at the University of Bath and ULCC Digital Archives department