Understanding PageRank
Query-dependent ranking models such as TF-IDF and BM25 are not sufficient for web search because they mainly measure how closely the terms in a query match t...
Information Retrieval
Relevance Feedback and Query Expansion
The problem of a pure keyword matching approach is that the systems can’t handle synonymy issue. For example, you might search for “python” meaning the progr...
Langauge Models for Information Retrieval
In information retrieval (henceforth IR), the language modeling approach is a form of probabilistic retrieval. Unlike traditional probabilistic methods, whic...
Systematic Evaluation for Information Retrieval: MAP and nDCG
The effectiveness (or accuracy) of an information retrieval system refers to how well it ranks relevant documents higher than non-relevant ones. Evaluating t...
Understanding BM25 in Text Retrieval
When you type a query into a search engine, it finds documents that contain your keywords. The problem is: how do you order those documents from most to leas...
Building Korean Query Auto-completion using Elasticsearch
Query auto-completion (QAC) is a feature that suggests completions for a user’s input query. It tries to guess what you’re about to type and throws out sugge...
Building Faceted Search using Elasticsearch
Faceted search Faceted search is a type of search that enables users to narrow down search results by applying multiple filters based on predefined facets, w...