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What is Neo4j

Handbook of Research on AI and Machine Learning Applications in Customer Support and Analytics
A highly scalable graph database management system designed to efficiently store, manage, and query highly connected data using the graph data model.
Published in Chapter:
Sequence Graph-Based Query Auto-Suggestion (SGQAS)
Soumya George (St. George's College Aruvithura, India)
DOI: 10.4018/978-1-6684-7105-0.ch018
Abstract
Query autosuggestion or auto-completion is a query prediction service that returns suggested queries for text-based queries when users type in the search box. It is a search-assistant feature of almost all search engines that helps users complete the queries without typing the entire search query. The process of query auto-suggestion typically involves analyzing the user's partial query and generating a list of suggestions based on factors such as popular search terms, the user's search history, and the search context. The suggestions are then displayed to the user in real-time, often in a drop-down menu or other interface types, allowing them to select and refine their search query easily. This chapter proposes a content-based query auto-suggestion using a graph-based word sequence representation of documents using a knowledge graph. It uses the whole sequence of all entered query terms to retrieve the names of all nodes connected to the end node of the entered path sequence of query terms to provide user suggestion queries.
Full Text Chapter Download: US $37.50 Add to Cart
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Extending Graph Databases With Relational Concepts
The most widely used Graph Database Management System.
Full Text Chapter Download: US $37.50 Add to Cart
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