Publication

Abstract : Database management systems usually allow partial text lookups using LIKE clauses and Regular Expressions. However, LIKE clauses and regular Expressions tend to underperform on larger datasets. They lack in performance as databases need to check the table to find whether there is the same word pattern as in regular expressions or as in LIKE statement. But it is difficult to have an efficient search query if we use regular expressions or LIKE Statements. If we use LIKE operator on the un-indexed column it would be extremely difficult to find out the matches because it needs to fully scan the columns. If the column is indexed then matching can be better than fully scan as matching can be performed against index keys. In worst case LIKE operator may have leading wildcards that require every index to be checked. Due to these limitations we have, we need to use another method which is efficient and flexible and there comes the full-text search where indexes are formed by words(from the words in the columns where the full-text search is enabled). Full-text search can be extended by incorporating semantics. By incorporating operators which support semantics [7], the search can be made more fruitful. Our proposed work will incorporate semantics-related operators in full-text search in PostgreSQL.