Latent semantic indexing - Part I (This is a pageholder only. The article will be published later)

NOTE: Since the upload of the examples, I have received a lot of requests for publishing the code and the article. Please expect a delay. Please bear with me.

Back to homepage This article will explain latent semantic indexing and show its demo implementation in C# .NET. This is Part-1 (the basics). The future version(s) will focus on scalability, precision, configuration and usability. Work related to Part 1 has been completed and will be published in some time. Please check this page again later. Examples from a sample collection of documents Simple search query w.r.t. contents in the sample. Show the matching documents. Rank approximation: 35% of collection The same query, but see the document in highlighted result. The document mentions word "fighting" which is synonymous to "clash". (Of course, the collection must have enough content to be able to establish synonymy) Rank approximation: 35% of collection Another random query that just occurred to me. The word "people" is present in the documents. The word "convince" does not occur in the highlighted document. But, interestingly, it ranks documents related to "social engineering" Rank approximation: 35% of collection Home