Enhancing Big Data Retrieval: A Comparative Analysis of Standard and Three-Level Indexing Techniques Using Dictionary Words Dataset
Keywords:
Big Data Retrieval, Indexing Techniques, Three-Level Indexing, Standard Indexing, Comparative Analysis, Dataset, Dictionary Words, Retrieval Performance, Efficiency, Scalability, Information Extraction, Linguistic DatasetsAbstract
Utilizing a large dataset of dictionary words, this study examines the way three-level indexing approaches perform when compared to traditional indexing techniques for improving big data retrieval. The research is concerned with assessing the retrieval effectiveness, efficiency, and scalability of these indexing systems in the context of managing huge datasets. The dictionary terms dataset will be subjected to standard indexing and three-level indexing as part of the experimental framework, and the retrieval accuracy and efficiency metrics will be subjected to a thorough comparison study. Particularly in the context of linguistic datasets, the findings provide helpful information on optimizing big data retrieval strategies. This study emphasises the need of sophisticated indexing techniques for organizing and gleaning useful data from huge databases.
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