IP Intelligence on Reddit Banned Domains

One useful application of the Minerazzi’s URL Scoring Tool we just launched consists in doing some IP intelligence on a list of banned domains. Usually, those with a similar or common IP are in a shared hosting environment or have a common ownership, or both. This can be another piece of information that could help you identify those behind a set of domain names.

To do this, just google [banned domains] and follow a result that points to a list of domain names banned by a web property. Then paste the list in the MUST textarea and submit it. You may want to be sure the URLs are carriage return delimited (crd). In general, you could do the same analysis for lists of parked domains, hacker sites, registrar companies, affiliate program urls, etc.

Here is the result of checking this old list of Banned Domains by Reddit. To properly interpret the results, visit  our tool’s page.


Status Extracted URL IP Tested URL
http://xeducation.info xeducation.info
http://funny-on-youtube.com funny-on-youtube.com
200 http://echomon.co.uk echomon.co.uk
200 http://www.imagetwist.com http://www.imagetwist.com
200 http://www.imageporter.com http://www.imageporter.com
200 http://blogs.discovermagazine.com blogs.discovermagazine.com
200 http://news.discovery.com news.discovery.com
200 http://www.sciencedaily.com http://www.sciencedaily.com
200 http://imgflash.com/ http://www.imgflash.com
200 http://www.globalpost.com http://www.globalpost.com
200 http://www.businessweek.com http://www.businessweek.com
405 http://bit.ly/ bit.ly/
200 http://medicalxpress.com/ http://www.medicalxpress.com
200 http://phys.org/ http://www.phys.org
200 http://www.theatlantic.com http://www.theatlantic.com
200 http://www.theatlanticcities.com http://www.theatlanticcities.com
200 http://www.thewire.com/ http://www.theatlanticwire.com

Quantum Database Searches: The Next Frontier

Learning about Grover’s Algorithm: Quantum Database Search.

Useful References:

  1. Grover, L. K. (1996). A fast quantum mechanical algorithm for database search.
  2. Grover, L. K. (1997). Quantum Mechanics helps in searching for a needle in a haystack Phys. Rev. Lett. 79 (1997) 325.
  3. Lavor, C., Manssur, L.R.U., and Portugal, R. (2008). Grover’s Algorithm: Quantum Database Search.
  4. Wikipedia. Grover’s algorithm.

XOR and XNOR Searches: Applications to IR, Search Marketing, and Web Mining

This is a follow up on the Beauty of XOR and XNOR searches post, describing possible applications of these search modes to Information Retrieval, Search Marketing, and Web Mining. The post is a snippet taken from http://www.minerazzi.com/help/xor-xnor.php

Enjoy it.

An IR researcher can test the performance of an LSI algorithm with a sample of documents retrieved through XOR and XNOR searches. Said sample should be rich in co-occurrence cases. Using a similar procedure, search marketers or Web intelligence specialists can identify sets of documents that emphasize keywords somehow related through different co-occurrence paths.

An interesting application consists in extracting all the unique terms (or just the high frequency ones) from a text source and constructing an XOR query with these. We may refer to this as XORing a text source. This should help one identify a network of co-occurrence paths over a collection and which documents might be relevant to specific combination of terms from the original source.

The text source can be a title, description, abstract, or paragraph of a document, or even an entire document. However, XORing a large document might be computer-intensive.

A similar exercise can be done by XNORing a text source. In both cases, the resultant output can be used to identify prospective competitors; i.e., documents relevant to similar concepts or belonging to companies within the same business space.

We are currently testing the XOR and XNOR search modes as a query disambiguation strategy.

PS. Today, 1-9-2014, we added new material that discusses these search modes for disambiguation and clustering. :)

The Beauty of XOR and XNOR Searches: Co-Occurrence and LSI

As part of the development of Minerazzi, we have published an article explaining two of our search modes: XOR and XNOR. Additional articles explaining other modes will soon follow.

We believe that IR and SEO practitioners will find these search modes particularly useful.

The beauty of XOR and XNOR searches is that these allow users to run complex co-occurrence searches in a straightforward manner. This is important as Latent Semantic Indexing information is related to term-term co-occurrence relationships.