4 Things You Should Know About Semantic Search



Semantic search is one concept that is all set to redefine search as we know it. Based on principles of Natural Language Processing and machine learning, it is indeed the future of search. This article looks into facts about semantic search that you should know.

If you are even remotely familiar with the trends from the world of search, you would agree that semantic search is the latest buzz word. It is redefining search in a big way. In fact, it is the technology that changed the way we look at search and has drastically affected the level of relevancy and accuracy. So, how does it work and what makes it such a novel approach? If the concept really interests you, here are 4 facts that will help you discover more about it.

Before we move on to the facts, let’s have a quick look at how we can define it.

Techopedia defines it as follows:

Semantic search is a data searching technique in a which a search query aims to not only find keywords, but to determine the intent and contextual meaning of the words a person is using for search.

On similar lines, we have another definition from TechTarget

Semantic search is an approach to finding content on the internet that anticipates the intention behind the user’s query. The goal of semantic search is to provide the end user with the most relevant search engine results possible.

Now, moving on to the quick factsheet…


Fact #1: The concept Behind It


The definition of semantic search makes it sound like an intelligent technology that can understand user’s intent and the context of the query. So, how does all of it work? Let’s try to figure out…

Given below is a flowchart of the query analysis process of semantic search

Concept Identification

|
Identification of Sentence Boundary
|
POS Tagging
|
Chunking
|
Named Entity Extraction
|
Ontology Matching
|
Query Expansion
|
Sentiment Analysis
|
Consolidation


The process begins with concept identification which identifies the concept of the query. The sentence boundary detection recognizes the start and end of the sentence. Next, POS tagging tags the words in the sentence into their respective parts of speech. Then the words are matched with the in-built domain vocabulary (ontology) for a match. Next the text is analyzed for Named entities with Named entity extraction and they are next chunked together. Next we have Query Expansion in which the query is reformulated to improve retrieval performance. At this stage, it is decided which query will be shown higher up on the results page. Finally, the query is subjected to sentiment analysis and the consolidated and semantically rich results are presented to the user.

Fact #2: Application


Search can be classified into 2 broad categories – navigational and research-based. While the former is used to help the user navigate through a website or an app, the latter is used to fetch documents and information for a specific purpose, research being a primary example.

Semantic search has its application in research based search, and is highly relevant in two major domains today – medical research and enterprise search. Both these domains have a comprehensive collection of data that needs to be analyzed for information retrieval.

Needless to say, the every successful enterprise search tool and the tools used for research are based on semantic search.

Fact #3: Origin


Semantics is derived from a Greek word which means ‘meaning’. The semantic concept began in 1971 with Robert W. Floyd. The source of semantic search, as we know it today, is a result of the evolution of the semantic web that was built using the principles of ontology. It all began with a paper written by R. Guha published in 2003. However, it was only in 2013 that it saw its first application and it has created history ever since.

Fact #4: Biggest Advantage


The most rewarding experience of using a semantic search-based platform is that it goes on to redefine the user experience by understanding the intent of the user when he is typing in a query.

With its introduction, it has become not just possible but easy to deal with the large quantities of unstructured data that is common to enterprises. Even in the field of research, it has made it possible to dig deep and get access to more information than ever. In other words, it provides the user more information than he expects, thus increasing the user satisfaction.

Before we sign offHealth Fitness Articles, we shall leave you with another fact. It’s interesting to note that the most basic difference between semantic search and normal search is the higher level of accuracy that the former offers. It goes beyond the exact words you type in to fetch you results that normal search can never provide.

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