Cross Validation Of Neural Network Applications For Automatic New Topic Identification

There are recent studies in the literature on automatic topic-shift identification in Web search engine user sessions; however most of this work applied their topic-shift identification algorithms on data logs from a single search engine. The purpose of this study is to provide the cross-validation of an artificial neural network application to automatically identify topic changes in a web search engine user session by using data logs of different search engines for training and testing the neural network. Sample data logs from the Norwegian search engine FAST (currently owned by Overture) and Excite are used in this study. Findings of this study suggest that it could be possible to identify topic shifts and continuations successfully on a particular search engine user session using neural networks that are trained on a different search engine data log

Neural network applications for automatic new topic identification on excite web search engine data logs

Bu çalışma, 12-17 Kasım 2004 tarihleri arasında Rhode Island[Amerika Birleşik Devletleri]’nde düzenlenen 67. Annual Meeting of the American Society for Information Science and Technology’de bildiri olarak sunulmuştur.The analysis of contextual information in search engine query logs is an important, yet difficult task. Users submit few queries, and search multiple topics sometimes with closely related context. Identification of topic changes within a search session is an important branch of contextual information analysis. The purpose of this study is to propose a topic identification algorithm using neural networks. A sample from the Excite data log is selected to train the neural network and then the neural network is used to identify topic changes in the data log. As a result, 76% of topic shifts and 92% of topic continuations are identified correctly.Sponsor: Amer Soc Informat Sci & Techno

A new integrated model for multitasking during web searching

Investigating multitasking information behaviour, particularly while using the web, has become an increasingly important research area. People s reliance on the web to seek and find information has encouraged a number of researchers to investigate the characteristics of information seeking behaviour and the web seeking strategies used. The current research set out to explore multitasking information behaviour while using the web in relation to people s personal characteristics, working memory, and flow (a state where people feel in control and immersed in the task). Also investigated were the effects of pre-determined knowledge about search tasks and the artefact characteristics. In addition, the study also investigated cognitive states (interactions between the user and the system) and cognitive coordination shifts (the way people change their actions to search effectively) while multitasking on the web. The research was exploratory using a mixed method approach. Thirty University students participated; 10 psychologists, 10 accountants and 10 mechanical engineers. The data collection tools used were: pre and post questionnaires, pre-interviews, a working memory test, a flow state scale test, audio-visual data, web search logs, think aloud data, observation, and the critical decision method. Based on the working memory test, the participants were divided into two groups, those with high scores and those with lower scores. Similarly, participants were divided into two groups based on their flow state scale tests. All participants searched information on the web for four topics: two for which they had prior knowledge and two more without prior knowledge. The results revealed that working memory capacity affects multitasking information behaviour during web searching. For example, the participants in the high working memory group and high flow group had a significantly greater number of cognitive coordination and state shifts than the low working memory group and low flow group. Further, the perception of task complexity was related to working memory capacity; those with low memory capacity thought task complexity increased towards the end of tasks for which they had no prior knowledge compared to tasks for which they had prior knowledge. The results also showed that all participants, regardless of their working memory capacity and flow level, had the same the first frequent cognitive coordination and cognitive state sequences: from strategy to topic. In respect of disciplinary differences, accountants rated task complexity at the end of the web seeking procedure to be statistically less significant for information tasks with prior knowledge compared to the participants from the other disciplines. Moreover, multitasking information behaviour characteristics such as the number of queries, web search sessions and opened tabs/windows during searches has been affected by the disciplines. The findings of the research enabled an exploratory integrated model to be created, which illustrates the nature of multitasking information behaviour when using the web. One other contribution of this research was to develop new more specific and closely grounded definitions of task complexity and artefact characteristics). This new research may influence the creation of more effective web search systems by placing more emphasis on our understanding of the complex cognitive mechanisms of multitasking information behaviour when using the web

Sistema de recomendação inteligente para uma plataforma de e-Learning

As plataformas de e-Learning são cada vez mais utilizadas na educação à distância, facto que se encontra diretamente relacionado com a possibilidade de proporcionarem aos seus alunos a valência de poderem assistir a cursos em qualquer lugar. Dentro do âmbito das plataformas de e-Learning encontra-se um grupo especialmente interessante: as plataformas adaptativas, que tendem a substituir o professor (presencial) através de interatividade, variabilidade de conteúdos, automatização e capacidade para resolução de problemas e simulação de comportamentos educacionais. O projeto ADAPT (plataforma adaptativa de e-Learning) consiste na criação de uma destas plataformas, implementando tutoria inteligente, resolução de problemas com base em experiências passadas, algoritmos genéticos e link-mining. É na área de link-mining que surge o desenvolvimento desta dissertação que documenta o desenvolvimento de quatro módulos distintos: O primeiro módulo consiste num motor de busca para sugestão de conteúdos alternativos; o segundo módulo consiste na identificação de mudanças de estilo de aprendizagem; o terceiro módulo consiste numa plataforma de análise de dados que implementa várias técnicas de data mining e estatística para fornecer aos professores/tutores informações importantes que não seriam visíveis sem recurso a este tipo de técnicas; por fim, o último módulo consiste num sistema de recomendações que sugere aos alunos os artigos mais adequados com base nas consultas de alunos com perfis semelhantes. Esta tese documenta o desenvolvimento dos vários protótipos para cada um destes módulos. Os testes efetuados para cada módulo mostram que as metodologias utilizadas são válidas e viáveis

Understanding Google: Search Engines and the Changing Nature of Access, Thought and Knowledge within a Global Context

This thesis explores the impact of search engines within contemporary digital culture and, in particular, focuses on the social, cultural, and philosophical influence of Google. Search engines are deeply enmeshed with other recent developments in digital culture; therefore, in addressing their impact these intersections must be recognised, while highlighting the technological and social specificity of search engines. Also important is acknowledging the way that certain institutions, in particular Google, have shaped the web and wider culture around a particular set of economic incentives that have far-reaching consequences for contemporary digital culture. This thesis argues that to understand search engines requires a recognition of its contemporary context, while also acknowledging that Google’s quest to “organize the world's information and make it universally accessible and useful” is part of a much older and broader discourse. Balancing these two viewpoints is important; Google is shaping public discourse on a global scale with unprecedentedly extensive consequences. However, many of the issues addressed by this thesis would remain centrally important even if Google declared bankruptcy or if search engines were abandoned for a different technology. Search engines are a specific technological response to a particular cultural environment; however, their social function and technical operation are embedded within a historical relationship to enquiry and inscription that stretches back to antiquity. This thesis addresses the following broad research questions, while at each stage specifically addressing the role and influence of search engines: how do individuals interrogate and navigate the world around them? How do technologies and social institutions facilitate how we think and remember? How culturally situated is knowledge; are there epistemological truths that transcend social environments? How does technological expansion fit within wider questions of globalisation? How do technological discourses shape the global flows of information and capital? These five questions map directly onto the five chapters of this thesis. Much of the existing study of search engines has been focused on small-scale evaluation, which either addresses Google’s day-by-day algorithmic changes or poses relatively isolated disciplinary questions. Therefore, not only is the number of academics, technicians, and journalists attending to search engines relatively small, given the centrality of search engines to digital culture, but much of the knowledge that is produced becomes outdated with algorithmic changes or the shifting strategies of companies. This thesis ties these focused concerns to wider issues, with a view to encourage and facilitate further enquiry.This thesis explores the impact of Google’s search engine within contemporary digital culture. Search engines have been studied in various disciplines, for example information retrieval, computer science, law, and new media, yet much of this work remains fixed within disciplinary boundaries. The approach of this thesis is to draw on work from a number of areas in order to link a technical understanding of how search engines function with a wider cultural and philosophical context. In particular, this thesis draws on critical theory in order to attend to the convergence of language, programming, and culture on a global scale. The chapter outline is as follows. Chapter one compares search engine queries to traditional questions. The chapter draws from information retrieval research to provide a technical framework that is brought into contact with philosophy and critical theory, including Plato and Hans-Georg Gadamer. Chapter two investigates search engines as memory aids, deploying a history of memory and exploring practices within oral cultures and mnemonic techniques such as the Ars Memoria. This places search engines within a longer historical context, while drawing on contemporary insights from the philosophy and science of cognition. Chapter three addresses Google’s Autocomplete functionality and chapter four explores the contextual nature of results in order to highlight how different characteristics of users are used to personalise access to the web. These chapters address Google’s role within a global context and the implications for identity and community online. Finally, chapter five explores how Google’s method of generating revenue, through advertising, has a social impact on the web as a whole, particularly when considered through the lens of contemporary Post-Fordist accounts of capitalism. Throughout, this thesis develops a framework for attending to algorithmic cultures and outlines the specific influence that Google has had on the web and continues to have at a global scale.Arts and Humanities Research Counci