1. Defining Semantic Search in the Context of Latent Semantic Indexing (LSI)
Semantic search refers to the process of understanding the intent and contextual meaning behind a user’s query and providing search results that match the user’s true search intention. In LSI, semantic search utilizes co-occurrence and contextual analysis to deliver more relevant search results.
2. Specifying the Context and Scope of Semantic Search with LSI
Semantic search with LSI involves analyzing the relationships between words and documents to decipher the context of search queries and documents.
3. Identifying Synonyms and Antonyms of Semantic Search
Synonyms of Semantic Search:
Contextual search, Meaning-based search.
Antonyms of Semantic Search:
Keyword-based search, Literal search.
4. Exploring Related Concepts and Terms
- Natural Language Processing (NLP): A field of AI that deals with the interaction between computers and human language, enabling machines to understand and process natural language queries.
- Information Retrieval: The science of obtaining relevant information from large collections of data, often used in search engines.
5. Gathering Real-World Examples and Use Cases of Semantic Search in Various Contexts
Example: In semantic search, if a user searches for “best smartphones,” the results will not only include web pages with the exact term “best smartphones” but also pages about highly-rated mobile devices, fulfilling the user’s intent.
6. Listing the Key Attributes and Characteristics of Semantic Search in LSI
Semantic search enhances search accuracy by considering the context, user intent, and relevance of search results.
7. Determining the Classifications or Categories of Semantic Search in LSI
Semantic search falls under the umbrella of advanced search algorithms used in LSI and modern search engines.
8. Investigating the Historical and Etymological Background of Semantic Search
The concept of semantic search emerged as search engines evolved from traditional keyword-based methods to understanding user intent.
9. Making Comparisons with Similar Concepts to Highlight Similarities and Differences
Comparing semantic search with traditional keyword-based search highlights the shift from matching exact keywords to understanding the context and meaning of queries, leading to more precise search results.
Closely related terms to Latent Semantic Indexing (LSI)
Co-Occurrence, Semantic Search, Topic Modeling, Keyword Variation, Latent Dirichlet Allocation (LDA)