Our accustomed systems of retrieving particular bits of information no longer fill the needs of many people. Searching traditional indexes of print publications has been aided by computerized databases, but still usually requires time-consuming serial searching of one database after the other, and then moving on to other methods of searching for internet sources. And what if the information being sought is a sound byte? A video clip? Yesterday's e-mail exchange between respected scientists? Artificial intelligence may hold the key to information retrieval in an age where widely different formats contain the information being sought, and the universe of knowledge is simply too big and growing too rapidly for successful searching to proceed at a human's slow speed.
B.2 Hierarchical k -means for semantic identifier The pseudo code of hierarchical k -means is detailed in in Algorithm 1. Algorithm 1: Hierarchical k -means.
In many search applications related to passage retrieval, text entailment, and sub-graph search, the query and each'document' is a set of elements, with a document
The document retrieval stage retrieves candidate documents related to the query, while the ranking stage re-ranks the documents using precise ranking scores.