Exploring The Value Of Folksonomies For Creating Semantic Metadata

Finding good keywords to describe resources is an on-going problem: typically we select such words manually from a thesaurus of terms, or they are created using automatic keyword extraction techniques. Folksonomies are an increasingly well populated source of unstructured tags describing web resources. This paper explores the value of the folksonomy tags as potential source of keyword metadata by examining the relationship between folksonomies, community produced annotations, and keywords extracted by machines. The experiment has been carried-out in two ways: subjectively, by asking two human indexers to evaluate the quality of the generated keywords from both systems; and automatically, by measuring the percentage of overlap between the folksonomy set and machine generated keywords set. The results of this experiment show that the folksonomy tags agree more closely with the human generated keywords than those automatically generated. The results also showed that the trained indexers preferred the semantics of folksonomy tags compared to keywords extracted automatically. These results can be considered as evidence for the strong relationship of folksonomies to the human indexer’s mindset, demonstrating that folksonomies used in the del.icio.us bookmarking service are a potential source for generating semantic metadata to annotate web resources

Folksonomic Tag Clouds as an Aid to Content Indexing

Social tagging systems have recently developed as a popular method of data organisation on the Internet. These systems allow users to organise their content in a way that makes sense to them, rather than forcing them to use a pre-determined and rigid set of categorisations. These folksonomies provide well populated sources of unstructured tags describing web resources which could potentially be used as semantic index terms for these resources. However getting people to agree on what tags best describe a resource is a difficult problem, therefore any feature which increases the consistency and stability of terms chosen would be extremely beneficial. We investigate how the provision of a tag cloud, a weighted list of terms commonly used to assist in browsing a folksonomy, during the tagging process itself influences the tags produced and how difficult the user perceived the task to be. We show that illustrating the most popular tags to users assists in the tagging process and encourages a stable and consistent folksonomy to form.Comment: SIGIR 2009 Workshop on Search in Social Media (SSM 2009

Callimachus DL: using semantics to enhance search and etrieval in a digital library.

Proceedings of: First World Summit on the Knowledge Society, (WSKS 2008), Athens, Greece, September 24-26, 2008Among the challenges of classifying, locating and accessing knowledge in Digital Libraries tackling with the huge amount of resources the Web provides, improving Digital Libraries by means of different strategies, particularly, using semantics remains a promising and interesting approach. In this paper, we present CallimachusDL, a semantics-based Digital Library which provides faceted search, enhanced access possibilities and a proof-of-concept implementation.Publicad

Enhancing the online discovery of geospatial data through taxonomy, folksonomy and semantic annotations

Spatial data infrastructures (SDIs) are meant to facilitate dissemination and consumption of spatial data, amongst others, through publication and discovery of spatial metadata in geoportals. However, geoportals are often known to geoinformation communities only and present technological limitations which make it difficult for general purpose web search engines to discover and index the data catalogued in (or registered with) a geoportal. The mismatch between standard spatial metadata content and the search terms that Web users employ when looking for spatial data, presents a further barrier to spatial data discovery. The need arises for creating and sharing spatial metadata that is discoverable by general purpose web search engines and users alike. Using folksonomies and semantic annotations appears as an option to eliminate the mismatch and to publish the metadata for discovery on the Web. Based on an analysis of search query terms employed when searching for spatial data on the Web, a taxonomy of search terms is constructed. The taxonomy constitutes the basis towards understanding how web resources in general, and HTML pages with standard spatial metadata in particular, can be documented so that they are discoverable by general purpose web search engines. We illustrate the use of the constructed taxonomy in semantic annotation of web resources, such as HTML pages with spatial metadata on the Web

USING TAGS IN AN AIML-BASED CHATTERBOT TO IMPROVE ITS KNOWLEDGE

Nowadays, it is common to find on the Internet different conversational robots which interact with users simulating a natural language conversation. Among them, we can emphasize the chatterbots based on AIML language. In this paper we present an AIML based chatterbot that shows as its main contribution the use of tags and folksonomies. Thanks to its use, we can generate a context for each conversation, being able to maintain a state for each user in the system, and improving the adaptation capabilities of the bot

Enhancing the online discovery of geospatial data through taxonomy, folksonomy and semantic annotations

Spatial data infrastructures (SDIs) are meant to facilitate dissemination and consumption of spatial data, amongst others, through publication and discovery of spatial metadata in geoportals. However, geoportals are often known to geoinformation communities only and present technological limitations which make it difficult for general purpose web search engines to discover and index the data catalogued in (or registered with) a geoportal. The mismatch between standard spatial metadata content and the search terms that Web users employ when looking for spatial data, presents a further barrier to spatial data discovery. The need arises for creating and sharing spatial metadata that is discoverable by general purpose web search engines and users alike. Using folksonomies and semantic annotations appears as an option to eliminate the mismatch and to publish the metadata for discovery on the Web. Based on an analysis of search query terms employed when searching for spatial data on the Web, a taxonomy of search terms is constructed. The taxonomy constitutes the basis towards understanding how web resources in general, and HTML pages with standard spatial metadata in particular, can be documented so that they are discoverable by general purpose web search engines. We illustrate the use of the constructed taxonomy in semantic annotation of web resources, such as HTML pages with spatial metadata on the Web.http://www.sajg.org.za/index.php/sajgam2016Centre for Geoinformation ScienceGeography, Geoinformatics and Meteorolog