Exploring Semantic Tagging with Tilkut

Exploring Semantic Tagging with Tilkut

Sari Vainikainen (VTT Technical Research Centre of Finland, Finland), Pirjo Näkki (VTT Technical Research Centre of Finland, Finland) and Asta Bäck (VTT Technical Research Centre of Finland, Finland)
Copyright: © 2012 |Pages: 19
DOI: 10.4018/978-1-60960-774-6.ch007
OnDemand PDF Download:
$30.00
List Price: $37.50

Abstract

Social bookmarking is one of the earliest examples of social media services. In bookmarking services there are two main approaches for adding metadata: user-generated freely chosen tags and keywords based on taxonomies or semantic ontology. This chapter presents a social bookmarking service Tilkut that combines the benefits of both of these approaches. Tilkut utilizes both freely defined tags and semantic tag suggestions based on predefined ontology. This chapter describes two different versions of the service and user experiences from a small scale user study and long-term test use in real context. Work related knowledge sharing was selected as a primary use case for the second version. The results from the first user studies were used as the starting point when developing the second version of Tilkut. A survey and workshop were organised to get more information of the requirements for enterprise use. In this chapter, we explain our approaches to adding semantics to social bookmarking, present the experiences, and discuss future research directions.
Chapter Preview
Top

Background

Challenges with Tagging

A lot of the success of tags and tagging can be attributed to the freedom of being able to use any word as a tag. Tagging is typically flat: all tags are at the same level and any number (or a high number) of tags can be applied to a resource. This has some drawbacks for utilising them even for the users themselves and more so for applications that aim at utilising this information automatically.

Well-known and frequent challenges with tags are that people use different words to describe the same thing, or a word has several different meanings (polysemy). People may also describe things at various levels of detail – an expert in a subject will use more detailed and specific words, whereas others use more general words. Also different forms of the same word (singulars, plurals, typos) exist. (Golder, 2006)

In addition to differences in vocabularies there are also differences between people in how they tag and why they tag. Also, applications have different restrictions and support to tags, which naturally affects the user behaviour.

There are several research papers (Golder, 2006; Maala, 2007; Marlow, 2006; Xu 2006) that report studies of the type of tags people use. In these papers the work has been based mostly on Delicious2 or Flickr3 tags. In Delicious, the following tag categories have been identified: topic, type of referenced resource, proper name (person, company, product, event, and location), subjective tags (adjectives, ratings), self reference, toDo tags and time (Golder, 2006). In Flickr photo tags categories include place, time, event, name, action and camera (Maala, 2007). The results of these studies were used when defining the tag categories for our prototype.

When the aim is to utilise tags, different types of tags give different opportunities. Topics (like travel, semanticweb, cat, cars) can be used for analyzing users’ interests as well as characteristics of the tagged resource. Proper names can be used as an indication of interests as well, particularly when additional information related to them can be found on the web. In our approach, we developed methods for automatic analysis of tag categories and methods for adding semantics to different type of tags. The aim is to use this additional metadata for finding and combining similar resources.

Complete Chapter List

Search this Book:
Reset