GitHub repository: m-germain/OT1-Indexing_And_Querying_Text
Created: 2020-10-20T09:10:43Z
Description: We explore algorithmic strategies for making an index to efficiently access large amount of unstructured textual data. At the core of an information retrieval (IR) system we often find a data structure called the "inverted index" used to retrieve documents given words they may contain. For all information retrieval models -- from the simpler ones (e.g., vector space model,...) to the more advanced (e.g., language models,...) -- their performance depends mainly on the decisions made while making the index. Thus, we introduce the algorithms and data structures necessary for the construction of an efficient index.  We will also consider how vector space models can, in a way, capture meaning. In particular, we will see how hyper-dimensional calculus and random indexing can be used for query expansion.