An inverted index is an index data structure storing a mapping from content, such as words or numbers, to its locations in a document or a set of documents. In simple words, it is a hashmap like data structure that directs you from a word to a document or a web page.
There are two types of inverted indexes: A record-level inverted index contains a list of references to documents for each word. A word-level inverted index additionally contains the positions of each word within a document. The latter form offers more functionality, but needs more processing power and space to be created.
Suppose we want to search the texts “hello everyone, ” “this article is based on inverted index, ” “which is hashmap like data structure”. If we index by (text, word within the text), the index with location in text is:
hello (1, 1) everyone (1, 2) this (2, 1) article (2, 2) is (2, 3); (3, 2) based (2, 4) on (2, 5) inverted (2, 6) index (2, 7) which (3, 1) hashmap (3, 3) like (3, 4) data (3, 5) structure (3, 6)
The word “hello” is in document 1 (“hello everyone”) starting at word 1, so has an entry (1, 1) and word “is” is in document 2 and 3 at ‘3rd’ and ‘2nd’ positions respectively (here position is based on word).
The index may have weights, frequencies, or other indicators.
Steps to build an inverted index:
Fetch the Document
Removing of Stop Words: Stop words are most occuring and useless words in document like “I”, “the”, “we”, “is”, “an”.
Stemming of Root Word
Whenever I want to search for “cat”, I want to see a document that has information about it. But the word present in the document is called “cats” or “catty” instead of “cat”. To relate the both words, I’ll chop some part of each and every word I read so that I could get the “root word”. There are standard tools for performing this like “Porter’s Stemmer”.
Record Document IDs
If word is already present add reference of document to index else create new entry. Add additional information like frequency of word, location of word etc.
Repeat for all documents and sort the words.
Words Document ant doc1 demo doc2 world doc1, doc2
Advantage of Inverted Index are:
- Inverted index is to allow fast full text searches, at a cost of increased processing when a document is added to the database.
- It is easy to develop.
- It is the most popular data structure used in document retrieval systems, used on a large scale for example in search engines.
Inverted Index also has disadvantage:
- Large storage overhead and high maintenance costs on update, delete and insert.
- Difference between Inverted Index and Forward Index
- Neo4j Drop Index
- Neo4j Create Index
- Minimum Index Sum for Common Elements of Two Lists
- Index Mapping (or Trivial Hashing) with negatives allowed
- Count of index pairs with equal elements in an array
- Find the character in first string that is present at minimum index in second string
- Maximum sum of two elements whose digit sum is equal
- Altering a table to add a collection data type in Cassandra
- Updating MAP collection data type in Cassandra
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- Updating Set in Cassandra
- Updating a List in Cassandra
- Check if given string contains all the digits
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