Information Retrieval: Advanced Topics and Techniques
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| Title: | Information Retrieval: Advanced Topics and Techniques |
|---|---|
| Description: | In the last decade, deep learning and word embeddings have made significant impacts on information retrieval (IR) by adding techniques based in neural networks and language models. At the same time, certain search modalities such as neural IR and conversational search have become more popular. This book, written by international academic and industry experts, brings the field up to date with detailed discussions of these new approaches and techniques. The book is organized in three sections: Foundations, Adaptations and Concerns, and Verticals.Under Foundations, we address topics that form the basic structure of any modern IR system, including recommender systems. These new techniques are developed to augment indexing, retrieval, and ranking. Neural IR, recommender systems, evaluation, query-driven functionality, and knowledge graphs are covered in this section.IR systems need to adapt to specific user characteristics and preferences, and techniques that were considered too niche a few years ago are now a matter of system design consideration. The Adaptations and Concerns section covers the following topics: conversational search, cross-language retrieval, temporal extraction and retrieval, bias in retrieval systems, and privacy in search.While web search engines are the most popular information access point, there are cases where specific verticals provide a better experience in terms of content and relevance. The Verticals section describes eCommerce, professional search, personal collections, music retrieval, and biomedicine as examples. |
| Authors: | Omar Alonso, Ricardo Baeza-Yates |
| Resource Type: | eBook. |
| Subjects: | Computer science, Information retrieval, Information storage and retrieval systems, Information behavior |
| Categories: | COMPUTERS / System Administration / Storage & Retrieval, COMPUTERS / Data Science / General, COMPUTERS / Data Science / Machine Learning |
| Database: | eBook Collection (EBSCOhost) |
| FullText | Links: – Type: ebook-pdf – Type: ebook-epub Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Information Retrieval: Advanced Topics and Techniques – Name: Abstract Label: Description Group: Ab Data: In the last decade, deep learning and word embeddings have made significant impacts on information retrieval (IR) by adding techniques based in neural networks and language models. At the same time, certain search modalities such as neural IR and conversational search have become more popular. This book, written by international academic and industry experts, brings the field up to date with detailed discussions of these new approaches and techniques. The book is organized in three sections: Foundations, Adaptations and Concerns, and Verticals.Under Foundations, we address topics that form the basic structure of any modern IR system, including recommender systems. These new techniques are developed to augment indexing, retrieval, and ranking. Neural IR, recommender systems, evaluation, query-driven functionality, and knowledge graphs are covered in this section.IR systems need to adapt to specific user characteristics and preferences, and techniques that were considered too niche a few years ago are now a matter of system design consideration. The Adaptations and Concerns section covers the following topics: conversational search, cross-language retrieval, temporal extraction and retrieval, bias in retrieval systems, and privacy in search.While web search engines are the most popular information access point, there are cases where specific verticals provide a better experience in terms of content and relevance. The Verticals section describes eCommerce, professional search, personal collections, music retrieval, and biomedicine as examples. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Omar+Alonso%22">Omar Alonso</searchLink><br /><searchLink fieldCode="AR" term="%22Ricardo+Baeza-Yates%22">Ricardo Baeza-Yates</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+science%22">Computer science</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Information+storage+and+retrieval+systems%22">Information storage and retrieval systems</searchLink><br /><searchLink fieldCode="DE" term="%22Information+behavior%22">Information behavior</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+System+Administration+%2F+Storage+%26+Retrieval%22">COMPUTERS / System Administration / Storage & Retrieval</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+General%22">COMPUTERS / Data Science / General</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+Machine+Learning%22">COMPUTERS / Data Science / Machine Learning</searchLink> |
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| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 025.524 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Computer science Type: general – SubjectFull: Information retrieval Type: general – SubjectFull: Information storage and retrieval systems Type: general – SubjectFull: Information behavior Type: general Titles: – TitleFull: Information Retrieval: Advanced Topics and Techniques Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Omar Alonso – PersonEntity: Name: NameFull: Ricardo Baeza-Yates – PersonEntity: Name: NameFull: Omar Alonso – PersonEntity: Name: NameFull: Ricardo Baeza-Yates IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2025 – D: 11 M: 06 Type: profile Y: 2026 Identifiers: – Type: isbn-print Value: 9798400710513 – Type: isbn-electronic Value: 9798400710520 – Type: isbn-electronic Value: 9798400710537 Numbering: – Type: volume Value: 00060 Titles: – TitleFull: Information Retrieval: Advanced Topics and Techniques Type: main |
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