Natural Language Processing for Semantic Search – Tutors India
                     USE OF 
NATURAL  
LANGUAGE  
PROCESSING IN  
SEMANTIC 
An Academic presentation by
SDrE. NaAncyR AgCnesH, Head, Technical Operations, Tutors 
India  Group www.tutorsindia.com
Email: [email protected]
TOPIC 
DISCUSSION
Introduction
Semantic Search Reduces 
Searching  And Increases Finding
Semantic Research Is A 
Variable  Investment Worth 
Making For  Organizations
What Are Some Examples Of 
Semantic  Research?
Conclusion
INTRODUCTIO
N
Computer-assisted text analysis is known as natural  
language processing (NLP).
An aspect of NLP is the study of how someone uses and  
understands language.
The goal of this is to develop the tools and methods  
necessary for computer systems to comprehend, change,  
and perform a wide range of useful tasks using natural  
language.
contd..
.
Researches in NLP are currently focused on creating sophisticated 
NLP  systems that incorporate both the general text and a sizable 
portion  of the ambiguity and unpredictability of a language.
Computational linguistics frequently faces problems with speech  
recognition, word separation, and other concepts. In NLP, it has been  
usual practice to create statistical approaches for it (Bast et al., 
2016)
.
FIG 1. (NLP) NATURAL LANGUAGE 
PROCESSING
SEMANTIC SEARCH 
REDUCES  SEARCHING AND 
INCREASES  FINDING
Since its creation in the early 1990s, the essential 
search  engine has made tremendous 
advancements.
However, it has recently made tremendous strides  
toward providing much more nuanced and pertinent  
solutions with the use of artificial intelligence (AI)   
technologies like machine learning (ML) and natural  
language processing.
contd..
.
AI skills are added to search engines to develop semantic search. No  
longer are searches restricted to words and their definitions from  
dictionaries: Understanding the query's goal and describing the data 
such  that it is "suited for meaningful retrieval," as stated in Towards 
Data  Science, are necessary for semantic search” (Do et al., 2010) .
By learning from prior query results, Semantic Search uses machine  
learning to increase accuracy and relevance.
contd..
.
By using NLP, the searcher is able to formulate their inquiries as if they were 
speaking to  a human. They might spend less time coming up with the best 
keywords for a particular  search as a result.
Unlike its keyword-based predecessor, semantic search can handle informations 
from a  wide range of sources, including email, social media, documents, PDFs, 
images, video,  and audio.
This considerably expands the searcher's possibilities by enabling them to find what  
they're looking for using all of the resources at their disposal (Sheu et al., 2009) .
SEMANTIC RESEARCH IS A 
VARIABLE  INVESTMENT WORTH 
MAKING FOR  ORGANIZATIONS
There has never beena business that wouldn't
benefit from  obtaining quicker, more precise, and higher-
quality results.
By eliminating unnecessary information and only displaying  
the most correct answers, semantic search enables less  
searching and more discovery.
Consider ing the example of an underwater welder 
searching  for supplies to complete a task on a 1,500-foot-
deep oil rig in  the Gulf of Mexico.
contd...
A keyword search would only give up results pertaining 
to  welding, thereby omitting the multifaceted nature of 
this  endeavour.
The context of such a project would be recognised by a  
semantic search, together with the fact that the welder 
is  second in importance to the diver in the searcher's 
profile.
In addition to taking into account factors like working  
conditions and water currents, it would offer pertinent  
results, such as those from a hyperbaric chamber.
contd..
.
Semantic search may provide further business benefits by merging NLP 
 with an intuitive user interface and making it straightforward for 
anyone to  interact with and get the results they're looking for.
Fast access to accurate findings facilitates decision-making  and  
increases productivity in businesses of all sizes.
By combining unstructured data from many sources, semantic search  
may also aid in the expansion and success of enterprises (Kupiyalova 
et  al., 2020) .
WHAT ARE SOME 
EXAMPLES  OF SEMANTIC 
RESEARCH?
Interestingly, since the Hummingbird upgrade in 2013, 
Google  has been embracing semantic search to 
enhance its user  experience.
With this improvement, "conversational search" was  
introduced to its repertoire, meaning that the context of 
the  full query was taken into account rather than just 
certain  phrases.
Online retailer Zappos just integrated semantic search to  
their website to make it easier for customers to locate  
exactly what they're looking for.
contd...
The algorithm adapts the result to each customer's prior search data,  
according to the company's chief data scientist, in addition to 
understanding  the context of the search word (Wei et al., 2008) .
As a result, Zappos is in a position to offer each of its customers the 
results  that are specifically relevant to them.
Companies all around the world are turning to services like Microsoft Azure 
 and AWS Comprehend, which enable them to use the technologies 
without  having to build it themselves, as the advantages of semantic  
search  become more and more clear.
CONCLUSION
In order to ensure that no crucial information is  
overlooked, effectively using semantic search also 
 requires destroying any internal data silos that 
may  exist (Cotfas et al., 2019).
By making sure that employees  are forthcoming  
with the necessary information and that 
adequate  technical preparation is in place, 
organisations may  train their conceptual search 
engine to produce the  most informed and 
accurate results.
contd...
Nevertheless, much study remains to be done, despite the fact  that  
semantic search may seem to be a mature technology.
That is not to imply that we shouldn't start using it today in order to 
benefit  from its many benefits rather than waiting till technology reaches 
its full  potential: Semantic search may be used by companies of all 
sizes to help  them make decisions more quickly and thoroughly, enhance 
customer  experience, and increase revenue (Sangers et al., 2013) .
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