Semantic Search Trends in 2019

This term is certainly not new in the IT world – “Semantic Search”. The field of Semantic Search has become so important that a new article is being written on the topic every 25 minutes! So, what is semantic search? What makes it one of the most sought after technologies by enterprises today?

Semantic search is nothing but search technology that focuses on deriving the meaning of the query to fetch results, to ensure the results are relevant to the context of the query as well as the intent of the user. This concept is different from the traditional keyword based search which fetches search results on the basis of word or phrase matching.

 The fact that semantic search does not rely on keyword matching to fetch results, makes it highly effective for data that is not optimized whereas keyword based search can only work for optimized data. Today, organizations are embracing semantic search technology because organizational data is unstructured and hence, non-optimized, and so only the enterprise search tools powered by semantic technology, such as 3RDi Search and Coveo, can help enterprises today.

Today’s article is about Semantic web and technology advancements or trends in 2019 –there have been some exciting and interesting developments in this space like Innovative integration of additional Artificial Intelligence techniques such as Natural Language Processing (NLP) and Deep Learning over multiple web sources to find and check facts. Thomas Reuters introduced the Knowledge Graph feed. Companies across all the sectors including Retail, Health care, financial services are including AI knowledge graph, hard facts, interpretations and predications that leverage machine learning, Semantic technology and Natural Language Processing.

Creative minds and unstoppable advance technology teams today give enterprises increasingly incentive solutions to solve data challenges. AI is the buzz word these days and people relate or associate with movies like Terminator.

It’s been questioned and ask frequently why this Knowledge graph is so important? The AI knowledge graph can solve internal information challenges, such as safeguarding global information and making sense of it. In short, the knowledge is governed by intelligent agents than individual.

As of last year 2018, there was growing interest in learning techniques and this trend will continue in near future. The future will witness a broader acceptance for AI technologies – using natural language as its core – in the semantic search. Using specific phrases, for instance, when searching for information-content. Bootstrapping AI projects in companies means on one side to develop various skills, on the other side a strategy must be developed that tackles the fundamental question “make, buy, or outsource?”

Conclusion:

The future of new technologies relies on the way they remain relevant when many other different approaches have been suggested with different properties. In other words, the benefits of the Semantic Web and Linked Data need to become tools in the toolkit of developers in order to stay relevant. This means being efficient and robust with clear solutions.