Semantic Search Using Natural Language Processing – Tutors India

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USE OF NATURAL LANGUAGE PROCESSING IN SEMANTIC
SEARCH
An Academic presentation by Dr. Nancy Agnes,
Head, Technical Operations, Tutors India Group
www.tutorsindia.com Email info_at_tutorsindia.com
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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
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INTRODUCTION
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...
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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) .
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FIG 1. (NLP) NATURAL LANGUAGE PROCESSING
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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...
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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...
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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) .
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SEMANTIC RESEARCH IS A VARIABLE INVESTMENT WORTH
MAKING FOR ORGANIZATIONS
There has never been a business that wouldn't bene
fit 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...
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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...
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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) .
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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...
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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.
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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...
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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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