SEO

EyePlorer : a New Approach to Semantic Search

EyePlorer developed by German company Vionto.com visualizes knowledge graphs (k-graphs) derived from Wikipedia content that can be interactively explored.

The knowledge graph consists of eyespots representing concepts that are connected to your topic. For better orientation those eyespots are clustered. If you want to know how any eyespot is connected to your topic, just click on it.

Let’s have a look at how it works.

Let’s type [Search engine optimization] – while we type, terms will be suggested to us:

eyeplorer suggestions EyePlorer : a New Approach to Semantic Search


With [Search engine optimization] we get the following eyePlorer (notice green cluster that seems to associate Danny Sullivan with black hat):

eyeplorer seo EyePlorer : a New Approach to Semantic Search

If you click on “image search” spot there, you will get a message that explains how “image search” is connected to your query.

SEO is one of the key Web Marketing activities and can target different kinds of searches, including image search, local search, and industry-specific vertical search engines.

eyeplorer image search EyePlorer : a New Approach to Semantic Search

You can click “more” to get more facts about each eyespot. Also, try double-clicking on an eyespot and you’ll see which other eyespots it is related to:

eyeplorer related EyePlorer : a New Approach to Semantic Search

Or you can explore two related concepts and see only eyespots related to both of them (for that, drag any eyespot to the red + button in the middle).

eyeplorer 2 EyePlorer : a New Approach to Semantic Search

You can also exclude any cluster from the eyePlorer by dragging it from the circle.

The fun doesn’t stop here. You can also save notes right from the eyePlorer by dragging the fact to the notepad to the right.

eyeplorer save EyePlorer : a New Approach to Semantic Search

So what does the tool actually do? Most importantly, it implements a different search model (that, again, may change how we understand and implement SEO). What do you think?

Here is a video I found on Youtube on how the tool is going to work:

Many thanks Webnauts to for showing me the tool.

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Ann Smarty is the blogger and community manager at Internet Marketing Ninjas. Ann's expertise in blogging and tools serve as a base for her writing, tutorials and her guest blogging project, MyBlogGuest.com.
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4 thoughts on “EyePlorer : a New Approach to Semantic Search

  1. my eyes(pots) tell me that this visualization is pretty much a useless toy with nice colors – just like a cake with too much icing.

    just tried to find something about ” tail”.
    all eyespots refer to a single wikipedia page. Clusters make pretty much no sense at all: what’s the rationale for a “work” cluster.

    Some results are completely missing: where is a reference for the Unix tool “tail”???? cf http://en.wikipedia.org/wiki/Tail_(Unix)

    pretty disappointing in my eyes(pots)

    mark

  2. @mark: Yes that makes sense. The technology looks very poor and crappy. Its based on simple pattern matching and collocation analysis. The technology behind is also based on a simple activation spreading network which produces the k-graphs – the term here is k-matrix. The graphs are static and precalculated. We must calculate the whole graph new if something changes. Also the content base must contain valid text. The system is not be able to search in webpages, cause the lingustic system behind must analyse sentences. Webpages has quite more problematic text patterns. Sentences are not simple to recognize and extract, it is very domain dependend. Also there is not idea yet to prevent spam and SEO stuff.The system also has yet no ability to recognize invalid statements (Subject-Predicate-Object) like “A headset is human”. In opposite to the suggestion of the name (vionto == visual ontology) the system does not based on any ontology which follows an official definition.

    Your problem with “tail” comes from the relevance and the denotation of the term. The term has much different concepts with which the technology behind is not able to work and distinguishable correctly. The system behind has no idea of “tail”. “tail” is only a term which is associated with some other terms. Also “tail” is not only a thing but also a verb (to tail after someone, to tail after someone, to keep one’s tail up…)

  3. Thanks a lot for this very good overview article on eyePlorer.com, we’re glad that you enjoy working with the tool. By the way, we’re currently implementing several new features to be released in a few weeks.