Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Review literature on relatedness measures based on linked data #16

Open
gopalkoduri opened this issue Mar 4, 2014 · 4 comments
Open
Milestone

Comments

@gopalkoduri
Copy link
Collaborator

In order to compute similarity/relatedness between artists, we must leverage the links between different artists, not just the direct ones, but indirect ones as well. Eg: In a->b->c, a is directly linked to b, but indirectly linked to c.

Review literature on semantic relatedness measures (need not be for music) based on linked data.

@gopalkoduri gopalkoduri added this to the Research milestone Mar 4, 2014
@mpetyx
Copy link
Owner

mpetyx commented Mar 5, 2014

I have some experience with that, since that is closely related to inference and reasoning.
Owl is also one of my areas of research, thus I think I could help.
If you have any specific paper in mind, I would to study it also, otherwise I will start looking if there is anything similar.

@gopalkoduri
Copy link
Collaborator Author

I'm reading these papers:

  1. dbrec -- Music recommendations using DBpedia
  2. Hey! Ho! Let's Go! Explanatory music recommendations with dbrec
  3. Measuring semantic distance on linking data and using it for resources recommendations

I would recommend the following papers (which I will not go through):

  1. Media meets semantic web - How the BBC uses DBpedia and Linked data to make connections
  2. Development and application of a metric on semantic nets
  3. Semantic distance in wordnet: An experimental, application oriented evaluation of five measures

@mpetyx
Copy link
Owner

mpetyx commented Mar 5, 2014

ok thanx!

@mpetyx
Copy link
Owner

mpetyx commented Mar 5, 2014

the last two references are from relatively old papers.
I will study them, but also search for more recent work.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants