44 research outputs found
Still a Lot to Lose: The Role of Controlled Vocabulary in Keyword Searching
In their 2005 study, Gross and Taylor found that more than a third of records retrieved by keyword searches would be lost without subject headings. A review of the literature since then shows that numerous studies, in various disciplines, have found that a quarter to a third of records returned in a keyword search would be lost without controlled vocabulary. Other writers, though, have continued to suggest that controlled vocabulary be discontinued. Addressing criticisms of the Gross/Taylor study, this study replicates the search process in the same online catalog, but after the addition of automated enriched metadata such as tables of contents and summaries. The proportion of results that would be lost remains high
Enhancing information retrieval in folksonomies using ontology of place constructed from Gazetteer information
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesFolksonomy (from folk and taxonomy) is an approach to user metadata creation where users describe information objects with a free-form list of keywords (âtagsâ). Folksonomy has have proved to be a useful information retrieval tool that support the emergence of âcollective intelligenceâ or âbottom-upâ light weight semantics. Since there are no guiding rules or restrictions on the users, folksonomy has some drawbacks and problems as lack of hierarchy, synonym control, and semantic precision. This research aims at enhancing information retrieval in folksonomy, particularly that of location information, by establishing explicit relationships between place name tags. To accomplish this, an automated approach is developed. The approach starts by retrieving tags from Flickr. The tags are then filtered to identify those that represent place names. Next, the gazetteer service that is a knowledge organization system for spatial information is used to query for the place names. The result of the search from the gazetteer and the feature types are used to construct an ontology of place. The ontology of place is formalized from place name concepts, where each place has a âPart-Ofâ relationship with its direct parent. The ontology is then formalized in OWL (Web Ontology Language). A search tool prototype is developed that extracts a place name and its parent name from the ontology and use them for searching in Flickr. The semantic richness added to Flickr search engine using our approach is tested and the results are evaluated
Molecule: sistema de organização e visualização de Tags
Diversas plataformas permitem que os utilizadores rotulem recursos
com tags e partilhem informação com outros utilizadores. Assim, foram
desenvolvidas vårias formas de visualização das tags associados aos recursos, com
o intuito de facilitar aos utilizadores a pesquisa dos mesmos, assim como a
visualização do tag space. De entre os vårios conceitos desenvolvidos, a nuvem de
tags destaca-se como a forma mais comum de visualização. Este documento
apresenta um estudo efetuado sobre as suas limitaçÔes e propÔe uma forma de
visualização alternativa. Sugere-se também uma nova interpretação sobre como
pesquisar e visualizar informação associada a tags, diferindo assim do método de
pesquisa direta do termo na base de dados que atualmente Ă© maioritariamente
utilizado. Como resultado desta implementação, obteve-se uma solução viåvel e
inovadora, o sistema Molecule, para vĂĄrios dos problemas associados Ă tradicional
nuvem de tags.Several platforms allow users to tag resources and share information.
Over time various forms of tags visualization have been developed in order to
facilitate the visualization of the tag space and the search and retrieval of
resources. The tag cloud stands out as the most common form of tags visualization.
This paper presents a study carried out on their limitations and proposes an
alternative. It also suggests a new interpretation on how to search and view
information associated with tags, thus differing from the method of direct search
term in the database that is currently used mostly. As a result of this
interpretation, a viable and innovative system was achieved, Molecule, that
overcome some of the problems associated with the traditional tag cloud
Semantic Social Network Analysis: A Concrete Case
In this chapter we present our approach to analyzing such semantic social networks and capturing collective intelligence from collaborative interactions to challenge requirements of Enterprise 2.0. Our tools and models have been tested on an anonymized dataset from Ipernity.com, one of the biggest French social web sites centered on multimedia sharing. This dataset contains over 60,000 users, around half a million declared relationships of three types, and millions of interactions (messages, comments on resources, etc.). We show that the enriched semantic web framework is particularly well-suited for representing online social networks, for identifying their key features and for predicting their evolution. Organizing huge quantity of socially produced information is necessary for a future acceptance of social applications in corporate contexts
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Classification design : understanding the decisions between theory and consequence
Classification systems are systems of terms and term relationships intended to sort and gather like concepts and documents. These systems are ubiquitous as the substrate of our interactions with library collections, retail websites, and bureaucracies. Through their design and impact, classification systems share with other technologies an unavoidable though often ignored relationship to politics, power, and authority (Fleischmann & Wallace, 2007). Despite concern among scholars that classification systems embody values and bias, there is little work examining how these qualities are built into a classification system. Specifically, we do not adequately understand classification construction, in which classification designers make decisions by applying classification theory to the specific context of a project (Park, 2008). If systems embody valuesâ particularly values that might either cause harm (Berman, 1971) or provide an additional means of communicating the creatorâs position (Feinberg, 2007)â we must understand how and when the system takes on these qualities. This dissertation bridges critical classification theory with design-oriented classification theory. Where critical classification theory is concerned with the outcomes of classification system design, design-oriented classification theory is concerned with the correct processes by which to build a classification system. To connect the consequences of classification system design to designersâ methods and intentions, I use the research lens of infrastructure studies, particularly infrastructural inversion (Star & Ruhleder, 1996) or making visible the work behind infrastructures such as classification systems. Accordingly, my research focuses on designersâ decisions and rethinks our assumptions regarding the factors that classification designers consider in making their design decisions. I adopted an ethnographic approach to the study of classification design that would make visible design decisions and designersâ consideration of factors. Using this approach, I studied the daily design work of volunteer classification designers who maintain a curated folksonomy. Using the grounded theory method (Strauss & Corbin, 1998), I analyzed the designersâ decisions. My analysis identified the implications of the designersâ convergences and divergences from established classification methods for the character of the system and for the connection between classification theory and classification methods. I show how the factorsâand the prioritization of factorsâthat these designers considered in making their decisions were consistent with the values and needs of the community. Therefore, I argue that classification designers have an important role in creating the values or bias of a classification system. In particular, designersâ divergence from universal guidelines and designersâ choices among sources of evidence represent opportunities to align a classification system to its community. I recommend that classification research focus on such instances of divergence and choice to understand the connection between classification design and the values of classification systems. The Introduction motivates the problem space around values in classification systems and outlines my approach in focusing on classification design. The Literature Review outlines the dominant theories in classification scholarship according to three elements of classification design: what decisions designers make, what information designers use in their decisions, and what skills designers apply to their decisions. In the Methods chapter, I introduce the site of my ethnographic research (The Fanwork Repository), detail my ethnographic methods, summarize the types of data I collected, and describe my grounded analysis. Three findings chapters examine one type of complex decision each: Names, Works, and Guidelines, respectively. In the fourth findings chapter, Synthesis, I define 10 factors designers considered across these complex design decisions. I then discuss how the factors figured into complex design decisions, how the factors overlapped and conflicted in design decisions, and how designers understood their role in making complex design decisions. In the Discussion chapter I connect the findings from the site of my ethnography to classification scholarship. In the Conclusion, I consider the contribution of examining classification systems as infrastructure, highlight the differences in accounts of classification design decisions made visible through classification theory and infrastructure studies approaches, and present suggestions for future research in classification design and the study of classification systems as infrastructure.Informatio
Semantic technologies: from niche to the mainstream of Web 3? A comprehensive framework for web Information modelling and semantic annotation
Context: Web information technologies developed and applied in the last decade
have considerably changed the way web applications operate and have
revolutionised information management and knowledge discovery. Social
technologies, user-generated classification schemes and formal semantics have a
far-reaching sphere of influence. They promote collective intelligence, support
interoperability, enhance sustainability and instigate innovation.
Contribution: The research carried out and consequent publications follow the
various paradigms of semantic technologies, assess each approach, evaluate its
efficiency, identify the challenges involved and propose a comprehensive framework for web information modelling and semantic annotation, which is the thesisâ original contribution to knowledge. The proposed framework assists web information
modelling, facilitates semantic annotation and information retrieval, enables system interoperability and enhances information quality.
Implications: Semantic technologies coupled with social media and end-user
involvement can instigate innovative influence with wide organisational implications that can benefit a considerable range of industries. The scalable and sustainable business models of social computing and the collective intelligence of organisational social media can be resourcefully paired with internal research and knowledge from interoperable information repositories, back-end databases and legacy systems.
Semantified information assets can free human resources so that they can be used to better serve business development, support innovation and increase productivity