{"product_id":"128633","title":"Vector Database Design and Construction ","description":"\u003ccenter\u003e\u003cdiv style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/tmgdisk01.cafe24.com\/images\/vs\/4172\/sv\/3jX1PGI0ge5YY62478fVFry6hoU9Mx.png?v=1765058552\" style=\"max-width:100%;max-height:10px\"\u003e\u003c\/div\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\n\n\u003cdiv style=\"width:95%\"\u003e\n\n\u003cdiv style=\"text-align:center;font-size:30px;font-weight:bolder;line-height:1.6em\"\u003e Vector Database Design and Construction \u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"border-bottom:1px;border-bottom-style:dotted;border-color:;padding-bottom:20px\"\u003e\u003ccenter\u003e\u003ctable align=\"center\" width=\"100%\"\u003e\u003ctbody style=\"border:0px\"\u003e\n\n\u003ctr\u003e\u003ctd align=\"center\" style=\"line-height:1.2em;text-align:center;font-size:18px;color:black;font-weight:bold;padding-bottom:20px;\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\u003ctr\u003e\u003ctd style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/image.yes24.com\/goods\/142771026\/XL\" style=\"max-width:100%;height:auto\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\u003c\/table\u003e\u003c\/center\u003e\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;{split_style6}padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e Description \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;word-break:break-all;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eBook Introduction\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e  \u003cdiv\u003eRecently, AI software companies like Palantir have emerged as prominent players in the defense and healthcare sectors, and at their core are data-driven design and advanced analytics. To maximize the performance of AI systems, it's essential to structurally define and efficiently utilize unstructured data. Key technologies supporting this include Vector DB, knowledge graph modeling, and ontology.\u003cbr\u003e In particular, Vector DB, which can quickly search for semantic similarity in unstructured data, and Graph DB, which can perform relationship-centered search, are essential elements for AI implementation.\u003cbr\u003e For our country to compete with advanced AI countries, it is crucial to develop the ability to structure and analyze data beyond AI development capabilities. This book provides a core guide to data-centric AI design, from the concepts of Vector DB and Graph DB to practical application.\u003cbr\u003e\n\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\u003cul\u003e  \u003cli\u003eYou can preview some of the book's contents.\u003cbr\u003e \u003cspan\u003ePreview\u003c\/span\u003e\n\n\u003c\/li\u003e\n\u003c\/ul\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eindex\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e \u003cb\u003eChapter 1.\u003cbr\u003e Vector Database Overview\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e __1.1 The Rising Star of AI\u003cbr\u003e __1.2 Understanding Vectors\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 2.\u003cbr\u003e Vector DBMS Types and Selection Criteria\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e __2.1 Vector DBMS Features\u003cbr\u003e __2.2 Types of Vector DBMS and Considerations for Selection\u003cbr\u003e __2.3 Comparison of Features by Vector DBMS Type\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 3.\u003cbr\u003e Generative AI Project Design Methodology\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e __3.1 Generative AI Project Execution Procedure\u003cbr\u003e __3.2 Data Analysis Preparation and Design Procedure\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 4.\u003cbr\u003e Data Analysis and Preparation\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e __4.1 Data Range\/Type Analysis\u003cbr\u003e __4.2 Data Requirements Analysis\u003cbr\u003e __4.3 Data Feature Analysis\u003cbr\u003e __4.4 Obtaining the dataset\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 5.\u003cbr\u003e Vector DataBase Schema Design\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e __5.1 Vector DB Schema Design\u003cbr\u003e __5.2 Collection Design\u003cbr\u003e __5.3 Vector Design\u003cbr\u003e __5.4 Meta Data Design\u003cbr\u003e __5.5 Relationship Design\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 6.\u003cbr\u003e Data retrieval\/response consistency verification\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e __6.1 Data Evaluation and Validation\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 7. RAG Overview and Performance Improvements\u003c\/b\u003e\u003cbr\u003e \u003cbr\u003e__7.1 RAG Overview\u003cbr\u003e __7.2 RAG Architecture\u003cbr\u003e __7.3 RAG Limits\u003cbr\u003e __7.4 RAG improvements (Advanced RAG, Modular RAG, Graph RAG)\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 8.\u003cbr\u003e Advanced RAG\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e __8.1 Advanced RAG Overview\u003cbr\u003e __8.2 Cleaning the source data\u003cbr\u003e __8.3 Adjusting the Retrieval Strategy\u003cbr\u003e __8.4 Adjusting Search Strategy\u003cbr\u003e __8.5 Collection separation\/distribution\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 9.\u003cbr\u003e Modular RAG\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e __9.1 Modular RAG Overview\u003cbr\u003e __9.2 Independent modularization\u003cbr\u003e __9.3 Various FLOW patterns\u003cbr\u003e __9.4 Reference - Modular RAG External Paper\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 10.\u003cbr\u003e Graph RAG - Knowledge-Based RAG\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e __10.1 Graph RAG Overview\u003cbr\u003e __10.2 Graph DB Modeling - Basic Data Modeling Structure\u003cbr\u003e __10.3 Graph DB Modeling - Data Divide Depth\u003cbr\u003e __10.4 Graph DB Modeling - Data Modeling Procedure\u003cbr\u003e __10.5 Graph DB Modeling - Data Retrieval\u003cbr\u003e __10.6 Ontology\u003cbr\u003e __10.7 Using Knowledge Graph in Graph RAG (Graph DB + Ontology)\u003cbr\u003e __10.8 Business Application Cases of Graph RAG (Defense, Medical, Legal)\u003cbr\u003e __10.9 Neo4j DB\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 11.\u003cbr\u003e Try the program\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e __11.1 Chroma DB - Vector DB\u003cbr\u003e ____11.1.1 Installing Chroma DB \u003cbr\u003e____11.1.2 Program Walkthrough with Python - Saving Chroma Embedding Data\u003cbr\u003e ____11.1.3 Program Follow-up with Python - Generating Response Information with OpenAI\u003cbr\u003e ____11.1.4 Follow the Program with Python - Chunking\u003cbr\u003e ____11.1.5 Follow the Program with Python - Sample Program\u003cbr\u003e __11.2 Neo4j DB - Graph DB\u003cbr\u003e ____11.2.1 Installing Neo4j DB\u003cbr\u003e ____11.2.2 Program Walkthrough with Python - Neo4j Embedding Data Storage\u003cbr\u003e ____11.2.3 Program Follow-up with Python - Haluciation Improvements with Neo4j\u003cbr\u003e __11.3 Utilizing Neo4J DB algorithm (creating a community)\u003cbr\u003e ____11.3.1 Installing the Neo4J Plug-In\u003cbr\u003e ____11.3.2 Program Walkthrough with Python - Creating a Graph Model (Internet News Data)\u003cbr\u003e ____11.3.3 Program Follow-up with Algorithm - Community Creation (Internet News Data)\u003cbr\u003e __11.4 FAISS - Library\u003cbr\u003e ____11.4.1 FAISS Installation\u003cbr\u003e ____11.4.2 Program Walkthrough with Python - FAISS Embedding Storage and Retrieval\u003cbr\u003e __11.5 CHAT System - RAG Environment\u003cbr\u003e ____11.5.1 Streamlit \u003cbr\u003e____11.5.2 Follow the program with Python - Simple CHAT program\u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eDetailed image\u003c\/b\u003e \u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cdiv\u003e\u003cimg src=\"https:\/\/image.yes24.com\/momo\/TopCate5155\/MidCate007\/515460393.jpg\" border=\"0\" alt=\"Detailed Image 1\"\u003e\u003c\/div\u003e\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003ePublisher's Review\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e \u003cb\u003eIt doesn't just stop at explaining the concept.\u003cbr\u003e Beyond that, examples are included to help you get started with a real-world Vector DB.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e * Chroma DB - Vector DB\u003cbr\u003e * Neo4j DB - Graph DB\u003cbr\u003e * Neo4j DB - Algorithm Utilization (Community Creation)\u003cbr\u003e * FAISS - Library\u003cbr\u003e * CHAT system - RAG environment\u003cbr\u003e -------------------------------------------------------------------------------\u003cbr\u003e * Vector DB is a database optimized for processing unstructured data, especially vector data.\u003cbr\u003e Vector DB handles data in a vector space, and each data is expressed as a high-dimensional vector.\u003cbr\u003e In other words, Vector DB models data in a multidimensional space of three or more dimensions through mathematical calculations.\u003cbr\u003e\u003cbr\u003e * Graph DB can analyze data based on complex relationship information and provide more accurate information or inference results for problems. \u003cbr\u003eIn addition to simple data retrieval, in-depth analysis using the connections between data is possible.\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e * This book aims to provide step-by-step explanations of the concepts of Vector DB, and then move on to practical Vector DB and Graph DB in the last chapter.\u003cbr\u003e\u003cbr\u003e \u003cb\u003eWhat kind of readers is this book for?\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e - AI analysts\/designers interested in the analysis\/design of AI unstructured data and data utilization strategies.\u003cbr\u003e -.\u003cbr\u003e AI researchers and developers who want to explore data modeling, optimization, and application methods based on Vector DB.\u003cbr\u003e -.\u003cbr\u003e Readers interested in structuring knowledge graphs using Graph DB from a data analysis perspective \u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e GOODS SPECIFICS \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eDate of issue:\u003c\/strong\u003e March 1, 2025\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003ePage count, weight, size:\u003c\/strong\u003e 288 pages | 152*225*20mm\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN13:\u003c\/strong\u003e 9791193747049\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN10:\u003c\/strong\u003e 119374704X \u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cspan\u003e\u003c\/span\u003e\n\n\u003c\/center\u003e\n\n\n\u003c\/center\u003e","brand":"LIBRAIRIE COREENNE","offers":[{"title":"Default Title","offer_id":43893156544554,"sku":"128633","price":30.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0683\/2750\/5962\/files\/3fb7093e1c556379e48b9e96d7673afc.jpg?v=1765390502","url":"https:\/\/librairie.coreenne.fr\/en\/products\/128633","provider":"LIBRAIRIE COREENNE","version":"1.0","type":"link"}