Semantic Web applications and social tagging Essay

Semantic Web is a vision of transformation of current web abundant with unstructured data into a web of data annotated with machine readable metadata (semantics of data) which can be processed directly and indirectly by computers [1]. Semantic Web applications include any web applications that can make sense of meaning in unstructured text or data.The aim of Semantic Web is to achieve and increase intelligence which includes stand-alone intelligence of web systems that can reason and infer new knowledge based on the meaning of the data as well as collective intelligence [2] that emerges from the collaboration and competition of many individuals and leads to computer-based decision making. The power of semantic web comes from the collective intelligence of its users. The examples of such activities include crowdsourcing, which is based on the idea that the crowd (a loosely connected group of people) on average is more intelligent than an individual and can collect large amounts of information and aggregate them to gain an accurate view of a topic [3]. Another form of collective intelligence is social tagging[4], when a community of users collaboratively creates and manages tags to annotate and categorize web content. Though usually users are free to choose any tag to annotate the content, the process creates a folksonomy [5], i.e., a common vocabulary shared by the community, which reflects similar semantic representations of words and concepts, even when the tags may vary across individuals. Such folksonomy can be further used to search against tagged resources and infer other knowledge on the annotated data and on the users themselves.
Collective creation of folksonomies may be a key to developing a Semantic Web, and can provide a number of advantages such as increased personalization of human-computer interaction [6], improved communication in software development [7], cultural and social adaptivity of web content [8] as well as increased intelligence of applications [9], and increased user satisfaction through engagement and gamification [10]. Already, social tagging has been proven to increase search precision in web search engines [11]. However, it is difficult to persuade web users other than in niche dedicated communities such as music or cinema fans, to tag web content consistently (efforts include the use of gamification techniques [12], etc.).
Social tagging has emerged as one of the best ways of associating metadata with web content. Tags can be key words or key phrases attached to documents or web objects (blog entries, photos, music, or videos) to describe the meaning (or semantic properties) of these objects [13]. Different kinds of tags may be used such as content-based, context-based, attribute, ownership, subjective (affective), organizational, purpose-based, factual, personal, self-referential, geographical, etc. [4]. Usually, humans add tags to the information they consider relevant and that information becomes semantic web content. This can be done manually or software can help by recommending most popular or semantically relevant tags. However, the manual approach can fail to provide a consistent tagging especially when the size of the tag vocabulary increases and the semantic knowledge of users diverge.