Lexical Similarity Measure

My last post described the Levenshtein's algorithm for finding the differences between two sequences which does so by means of "edit distance" metric.  Recently, I read an algorithm that utilizes the same metric to calculate the lexical similarity measure between two strings Li and Lj:

SM(Li, Lj ) := max(0 , (min( |Li|, |Lj| ) - ed(Li,Lj) ) / min(|Li|, |Lj|))

where

|Li| and |Lj| are the lengths of  Li and Lj ,
ed(Li, Lj) is the edit distance between Li and Lj

This method can be applied for comparing two set of strings as well. Details can be found in the paper: A. Maedche and S. Staab, "Measuring Similarity between Ontologies", Karlsruhe, Germany.

Levenshtein distance

Levenshtein distance, also known as edit distance, is a metric that measures the amount of differences between two given sequences. Wikipedia says the Levenshtein distance between two strings is given by the minimum number of operations needed to transform one string into the other, where an operation is an insertion, deletion, or substitution of a single character.

Usage: It is often used in applications that need to determine how similar, or different, two strings are, such as spell checkers.

Examples:
The Levenshtein distance between "kitten" and "sitting" is 3, since the following three edits change one into the other, and there is no way to do it with fewer than three edits:

1. kitten → sitten (substitution of 's' for 'k')
2. sitten → sittin (substitution of 'i' for 'e')
3. sittin → sitting (insert 'g' at the end).

Ontology Search Engines

I was looking for an ontology. I found that there exist many ontology search engines. Beauty of these search engines is that they only search ontologies unlike Google, and Yahoo which are general web search engines.

 

Why do we need ontology search engines?

They help to find the suitable ontologies for given user requirements so that reuse of knowledge bases can be made.

Examples

• SWOOGLE: An ontology search engine.
• SCARLET: Discovering relations between two concepts.
• WATSON: Search Ontology and Semantically Related Documents
  

Bloggers are the sensors

I prefer to say: "BLOGGERS ARE THE SENSORS". Sensors are triggered as soon as they sense the changes in the environment; bloggers are triggered as soon as they sense popular news or stories in the society. Similarly, sensors help humankind by providing their services. A number of BLOGGERS can easily direct the society by providing their views. Think from another angle, what if sensors of a machine don't work ? Answer is simple: the machine may not work properly. Similarly, if bloggers don't blog and don't raise social issues and views, society may not be directed the way it should be.

Definition: Feed distillation task

The task of identifying the most relevant feed for a given topic or query term is  known as the “feed distillation task”.

My Technical Blog gets momentum

I decided to accelerate my technical blog too. I'd started it since my MS thesis's proposal defense. However, I couldn't manage my time to update this blog for  a certain period. Now again its time to express technical stuffs to the blogosphere's visitors. Therefore, I've commenced posting technical stuffs...

How is blogosphere growing ?

According to some estimates, “the size of the Blogosphere continues to double every six months” and there are over seventy million blogs (with many that are actively posting). However, some studies indicate that of all these blogs and feeds, the ones that really matter are relatively few.