Semantic Search
Semantic search represents a sophisticated approach to information retrieval that seeks to understand the intent and contextual meaning behind a search query, rather than just matching keywords. It aims to improve search accuracy by considering the searcher's intent and the contextual significance of terms as they appear within the searchable dataspace. This method leverages technologies like machine learning and artificial intelligence to interpret natural language more accurately and deliver results that are conceptually relevant to the query. By doing so, semantic search can provide a more intuitive and effective search experience, returning content that aligns with the intended meaning rather than just the literal words used in the search. This technology is particularly useful in fields where precision and context are crucial, such as academic research or industry-specific databases.
What is Semantic Search?
Semantic Search refers to a search technique that aims to improve search accuracy by understanding the intent and contextual meaning of search queries, rather than just matching keywords. It employs natural language processing (NLP), machine learning, and knowledge graphs to interpret the relationships between words and concepts.In semantic search, the system evaluates the context of a query and uses data from various sources to provide more relevant results. This process involves:
- Understanding synonyms and variations of words
- Recognizing entities (people, places, things) and their relationships
- Considering user intent and context, such as location or previous searches
The goal is to return results that are not only relevant to the query but also align with the user's needs and the broader context in which the search occurs. Semantic search is commonly used in modern search engines, enabling them to deliver more precise and contextually aware answers.
- Snippet from Wikipedia: Semantic search
Semantic search denotes search with meaning, as distinguished from lexical search where the search engine looks for literal matches of the query words or variants of them, without understanding the overall meaning of the query. Semantic search seeks to improve search accuracy by understanding the searcher's intent and the contextual meaning of terms as they appear in the searchable dataspace, whether on the Web or within a closed system, to generate more relevant results.
Some authors regard semantic search as a set of techniques for retrieving knowledge from richly structured data sources like ontologies and XML as found on the Semantic Web. Such technologies enable the formal articulation of domain knowledge at a high level of expressiveness and could enable the user to specify their intent in more detail at query time.The articulation enhances content relevance and depth by including specific places, people, or concepts relevant to the query.
Related:
- Enterprise Search
- Keyword Search
- Natural Language Processing (NLP)
- Knowledge Graphs
- Contextual Search Algorithms
- Entity Recognition and Disambiguation
- Ontology-Based Information Retrieval
- Machine Learning in Search Technologies
- Data Annotation and Metadata Standards
- User Intent Analysis in Search Queries
- Advanced Querying Techniques
- Artificial Intelligence in Information Retrieval
External links:
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- Define semantic search and learn how it works. See how it differs from keyword search, its benefits, and how to get started using semantic search.\n…
- Semantic Search: What Is It & Why Does It Matter? — perplexity.ai
- Learn what semantic search is, how it works, why it can impact your business, and where product discovery tools, like Bloomreach Discovery, can help.
- Semantic Search | MongoDB — mongodb.com
- Learn about semantic search and MongoDB Atlas vector search utilizes this technology to help software developers and businesses.
- Open Semantic Search — opensemanticsearch.org
- What Is Semantic Search? | Ontotext Fundamentals — ontotext.com
- Semantic Search helps optimize the accuracy of the results and makes them highly contextual and personalized.
- What is Semantic Search? - GeeksforGeeks — geeksforgeeks.org
- A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.
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- Semantic search is the present and future, and it's important to have a good handle on what it is and how you can use it to your advantage. This post presents 5 strategies for getting started with semantic SEO.
- Semantic Scholar | AI-Powered Research Tool — semanticscholar.org
- Semantic Scholar uses groundbreaking AI and engineering to understand the semantics of scientific literature to help Scholars discover relevant research.
- Introducing semantic search: Bringing more meaningful results to Azure Cognitive Search — techcommunity.microsoft.com
- We are bringing state of the art AI capabilities to the “head” of our Azure Cognitive Search, the core search sub-system. In partnership with the Bing team, we have integrated their semantic search investments (100s of development years and millions of dollars in compute time) into our query infrastructure, effectively enabling any developer to leverage this investment over searchable content that you own and manage. We believe semantic search on Azure Cognitive Search offers the best combination of search relevance, developer experience, and cloud service capabilities available on the market.
- What is Semantic Search? —cohere.com
- In this LLM University chapter, you’ll learn how to use embeddings and similarity in order to build a semantic search model.