Johd – Vice Presidency for Science and Technology
Traditional search, commonly used in software and websites, relies on keyword appearances without understanding the meaning of the search term. This limited perspective often overlooks valuable results. In recent years, researchers have shifted towards semantic search, which intelligently conducts searches by understanding the meaning of the query.
Relevance for search engines is not merely finding pages with suitable words. Early search engines offered limited results. Over the years, engineers have developed better methods for achieving search results. Today, numerous factors affect relevance, and we will focus on semantic search engines in this project.
With the growth of technology, the volume of information stored by various organizations is increasing, leading to big data challenges. One of the most crucial services in retrieving stored information documents in organizational databases is the search engine.
A semantic search engine utilizes natural language processing (NLP) and semantic concepts to comprehend textual content. Unlike traditional keyword-matching search engines, semantic search engines understand concepts and relationships between words, allowing them to respond to more complex user queries meaningfully.
The importance of semantic search engines in big data stems from several advantages
Understanding Concepts: They grasp hidden concepts and relationships between data, resulting in more accurate search results
Improved Search Accuracy: By using semantic concepts, search engines provide more precise results, helping users quickly find needed information
Support for Complex Queries: They address ambiguous and complex queries, providing deeper comprehension of content, especially in environments with large, complex big data
Data Analysis Optimization: They enhance data analysis processes and extract more relevant information in big data contexts
Better Textual Relationships: They interpret texts effectively by understanding relationships between words, aiding users in comprehending complex texts easily
Meeting Diverse Needs: They cater to a wide range of complex queries and requests, addressing user needs more comprehensively
In summary, semantic search engines enhance efficiency and accuracy in data search and analysis, playing a vital role in understanding textual relationships
