semantics, ontology, search, web 2.0, web 3.0

There is a simple answer for this question: we still do not have the perfect search! There are some researchers, though, who suggest that such a thing is impossible because there will always be the user – specify information need is not an easy task. It means that we can develop a system that provides answers precisely but if the user does not know how to describe their needs we do not have the “perfect search.” For example, someone is trying to find a document that s/he knew it exists in his/her computer but s/he is not able to describe the document, its content, or its location. Therefore, uncertainty or incompleteness is a variable that should be considered in information retrieval (IR) research.

Trying to help users understand their information needs is a goal that IR systems must provide. Researchers are combining techniques from different areas so as to create IR systems more interactive. If we think that one of the main problems in retrieving the desired information is related to the user’s state of incompleteness, we first need to develop IR systems that help users understand their needs. Information seeking, for instance, is one of these areas. It focuses on the user behavior and how s/he searches for information (such information can be related to human and technological contexts). Basically, the main difference between information seeking and IR is that the former is more human-oriented whilst the latter is technology oriented. There are many works in information seeking that can help IR research so as to develop tools/mechanisms that can help users during the whole search process.

Another research area that has been used in order to enhance IR systems is ontologies – mainly after the advent of Semantic Web. There are many definitions of ontology in computer science – artificial intelligence (ontology is also a term used in philosophy – but this is not the focus here). We can think of ontology as a structure described in a formal language that allows computer systems understand its (semantic) content. This simple definition suggests that IR research can take advantage of this and implement more intelligent systems. The premise here is: If a system is able to understand document’s content it will be able to provide answers more precisely.

All of the above subjects are part of my current research and I hope in the near future present here how these techniques can be used together. Search research still requires a lot of work mainly because the amount of information is increasing exponentially (and I am not talking about just the Internet – even in our personal computers it is a reality). In my next posts I will try to show how new scientific technologies are being developed in order to help users understand their information needs and then find the desired information more quickly.