Indexing Documents

Mapping documents into a vector space.

The underlying space used to retrieve documents is a large ___________ where every __________________ in the language defines one _________________. Each document in the database can be given a location in the ________________described by this ___________________. Each query can also be mapped onto this ______________________.
In vector-based text retrieval, how does the overall frequency of a word in the language as a whole affect its importance within a query or document?
In simple vector-based text retrieval, dow do we measure the importance of a given word stem ('lemma') to the meaning of a document in which is occurs?
If you're building a web page with HTML, and you want to make it easy to find your web site, what metatags should you use, and (informally) how?

In standard vector-based text retrieval, how are queries mapped to documents in the database?
Name two factors that can influence the relevance ranking of a retrieved document.