---
title: "Information Retrival"
source: https://www.jemoka.com/posts/kbhinformation_retrival/
---

Information Retrival is trying to find material within large collections which is unstructured which satisfies an information need (of structured info).
Unstructured information has had a massive outburst after the millennium.
IMPORTANTLY: evaluating Information Retrival is based on Precision/Recall/F on information need and not the query.
For ranked system, we can come up with a curve of precision-recall curve by selecting increasing \(k\), or mean average precision.
Basic Terminology collection a set of documents&mdash;could by static, or dynamically added
goal retrieve documents with information relevant to the user&rsquo;s information need + to complete a task
information need information need is the actual information that is needed by a search; this is usually translated into a search query, which is actually used to search.
query query is a computer accessible form of text which searches to answer an information need.
information need: &ldquo;info about removing mice without killing them&rdquo; query: &ldquo;trapping mouse alive&rdquo; Stages of Interpolation user task =&gt; info need: we may not be looking for the right info info need =&gt; query: we may not be using the best methods to get the info we are looking for Motivation &ldquo;what&rsquo;s wrong with grepping?&rdquo;
we cannot afford to do a linear search over web-scale data a &ldquo;NOT&rdquo; query is non-trivial no semantics we have no ranking, so we don&rsquo;t know what&rsquo;s the &ldquo;best&rdquo; document Ranked Approaches Ranked Information Retrieval
