Why should you complement your traditional Boolean search queries with AI- driven semantic search?

Conventional, patent searching approach involves searching for keywords and phrases that are grouped in a query using Boolean and proximity operators. The queries are further combined with other queries using query-identifiers, thereby creating a query script which often run into more than 50+ strings. This process is tedious, and a lot of thought process goes into deciding the key terms, synonyms and classifications that are to go into the query. The traditional process albeit time-consuming, still ranks high on precision. It is also fraught with limitations, as missing out a single relevant term would result in missing out on important prior art.

With the exponential increase in the amount of information and working under time constraints, effectively bringing forth the right search results has become the need of the hour. This is where AI-driven semantic search helps.

Semantics implies something that conveys meaning or provides logic. Semantic search tries to improve search precision by recognizing the searcher’s purpose and providing more complete results. Searchers can also dig through data and find links that they may not have realised existed.

Why it has become imperative to club semantic search with your keyword searches?

A semantic search tool understands the different ways a concept is conveyed and in what perspective a term is used. The input paragraph is converted into a contextual search vector that looks at not just the direct matches but also similar matches. Here are a few reasons to supplement your Boolean queries with semantic searches.

PatSeer offers powerful semantic search which uses AI driven Natural Language Processing (NLP) engine — ReleSense. Simply paste a text up to 500 and add or remove the key concepts highlighted to search for patents related to your technology. The search engine reads the meaning of input text and maps the key terms provided against that context to give you the most relevant documents. Now, also strengthen your keyword query with the semantic search suggester offered by PatSeer. Give an input in the text field and the database looks up internal semantic Index for related terms.

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