How is the Perilog search algorithm different from Latent Semantic Indexing?
Perilog uses degree of co-occurrence between words in pairs as the data in its word-by-word matrix, while Latent Semantic Indexing (LSA) uses frequency of occurrence of words within a body of text in its word-by-document matrix. In LSA, word co-occurence is inferred by the fact that two words appeared in a document, regardless of their proximity. Perilog uses a word-by-word matrix to represent each body of text in a database (and another to represent each query), not one big matrix to represent all words and all bodies of text. In Perilog, a relevance value is found by comparing the query matrix to the document matrix as if they were vectors, where each dimension in the space represents the pair-wise contextual association of a pair of co-occurring words.
