Semantic Search and Recommendation Algorithm
This addresses the problem of slow and inaccurate search for users handling large datasets, but it appears incremental as it combines existing techniques.
The paper tackled the problem of inefficient information retrieval from large datasets by introducing a semantic search algorithm using Word2Vec and Annoy Index, resulting in enhanced speed, accuracy, and scalability with testing on datasets up to 100GB.
This paper introduces a new semantic search algorithm that uses Word2Vec and Annoy Index to improve the efficiency of information retrieval from large datasets. The proposed approach addresses the limitations of traditional search methods by offering enhanced speed, accuracy, and scalability. Testing on datasets up to 100GB demonstrates the method's effectiveness in processing vast amounts of data while maintaining high precision and performance.