1 option
AI-Powered Search.
- Format:
- Book
- Author/Creator:
- Grainger, Trey.
- Language:
- English
- Subjects (All):
- Web search engines.
- Artificial intelligence.
- Natural language processing (Computer science).
- Physical Description:
- 1 online resource (445 pages)
- Edition:
- 1st ed.
- Place of Publication:
- New York : Manning Publications Co. LLC, 2025.
- Summary:
- "Modern search is more than keyword matching. Much, much more. Search that learns from user interactions, interprets intent, and takes advantage of AI tools like large language models (LLMs) can deliver highly targeted and relevant results. This book shows you how to up your search game using state-of-the-art AI algorithms, techniques and tools."--Back cover.
- Contents:
- Introducing AI-powered search
- Working with natural language
- ranking and content-based relevance
- Crowdsourced relevance
- Knowledge graph learning
- Using context to understand domain-specific language
- Interpreting query intent through semantic search
- Signals-boosting models
- Pearsonalized search
- Learning to rank for generalizable search relevance
- Automating learning to rank with click models
- Overcoming ranking bias through active learning
- Semantic search with dense vectors
- Question answering with a fine-tuned large language model
- Foundation models and emerging search paradigms.
- Notes:
- Description based on publisher supplied metadata and other sources.
- Includes index.
- ISBN:
- 9781638350910
- 1638350914
- OCLC:
- 1493577215
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.