信息检索:算法与启发式方法(第2版)（“信息检索”课程的优秀教材）

.3.7 semantic networks 132
3.8 parsing139
3.9 summary 146
3.10 exercises146
4. cross-language information retrieval 149
4.1 introduction 149
4.2 crossing the language barrier 151
4.3 cross-language retrieval strategies 157
4.4 cross language utilities 170
4.5 summary ..178
4.6 exercises 179
5. efficiency181
5.1 inverted index 182
5.2 query processing 195
5.3 signature files 199
5.4 duplicate document detection 203
5.5 summary208
5.6 exercises209
6. integrating structured data and text 211
6.1 review of the relational model 215
6.2 a historical progression 222
6.3 information retrieval as a relational application 228
6.4 semi-structured search using a relational schema 245
6.5 multi-dimensional data model 250
6.6 mediators 250
6.7 summary 253
6.8 exercises 254
7. parallel information retrieval 257
7.1 parallel text scanning 258
7.2 parallel indexing 263
7.3 clustering and classification 270
7.4 large parallel systems 271
7.5 summary 272
7.6 exercises 274
8. distributed information retrieval 275
8.1 a theoretical model of distributed retrieval 276
8.2 web search 281
8.3 result fusion 284
8.4 peer-to-peer information systems 286
8.5 other architectures 289
8.6 summary 290
8.7 exercises 290
9. summary and future directions 291
references 299
index ... 331

.　　Information retrieval textbooks on the market are relatively unfocused, and we were uncomfortable using them in our
　　classes. They tend to leave out details of a variety of key retrieval models. Few books detail inference networks, yet an
　　inference network is a core model used by a variety of systems. Additionally, many books lack much detail on efficiency,
　　namely, the execution speed of a query. Efficiency is potentially of limited interest to those who focus only on
　　effectiveness, but for the practitioner, efficiency concerns can override all others.
　　Additionally, for each strategy, we provide a detailed running example. When presenting strategies, it is easy to gloss
　　over the details, but examples keep us honest. We find that students benefit from a single example that runs through the
　　whole book. Furthermore, every section of this book that describes a core retrieval strategy was reviewed by either the
　　inventor of the strategy (and we thank them profusely; more thanks are in the acknowledgments!) or someone intimately
　　familiar with it. Hence, to our knowledge, this book contains some of the gory details of some strategies that cannot be
　　found anywhere else in print.
　　Our goal is to provide a book that is sharply focused on ad hoc information retrieval. To do this, we developed a
　　taxonomy of the field based on a model that a strategy compares a document to a query and a utility can be plugged into any
　　strategy to improve the performance of the given strategy. We cover all of the basic strategies, not just a couple of them,
　　and a variety of utilities. We provide sufficient detail so that a student or practitioner who reads our book can implement
　　any particular strategy or utility. The book, Managing Gigabytes [Witten et al., 1999], does an excellent job of describing a
　　variety of detailed inverted index compression strategies. We include the most recently developed and the most efficient of
　　these, but we certainly recommend Managing Gigabytes as an excellent side reference. ..
　　So what is new in this second edition? Much of the core retrieval strategies remain unchanged. Since 1998, numerous papers were written about the use of language models for information retrieval. We have added a new section on language models. Furthermore, cross-lingual information retrieval, that is, the posting of a query in one language and finding documents in another language, was just in its infancy at the time of the first version. We have added an entire chapter on the topic that incorporates information from over 100 recent references.
　　Naturally, we have included some discussion on current topics such as XML, peer-to-peer information retrieval, duplicate
　　document detection, parallel document clustering, fusion of disparate retrieval strategies, and information mediators.
　　Finally, we fixed a number of bugs found by our alert undergraduate and graduate students. We thank them all for their
　　efforts.
　　This book is intended primarily as a textbook for an undergraduate or graduate level course in Information Retrieval. It
　　has been used in a graduate course, and we incorporated student feedback when we developed a set of overhead transparencies
　　that can be used when teaching with our text. The presentation is available at www.ir.iit.edu.
　　Additionally, practitioners who build information retrieval systems or applications that use information retrieval
　　systems will find this book useful when selecting retrieval strategies and utilities to deploy for production use. We
　　have heard from several practitioners that the first edition was helpful, and we incorporated their comments and suggested
　　additions into this edition.
　　We emphasize that the focus of the book is on algorithms, not on commercial products, but, to our knowledge, the basic
　　strategies used by the majority of commercial products are described in the book. We believe practitioners may find that a
　　commercial product is using a given strategy and can then use this book as a reference to learn what is known about the
　　techniques used by the product.
　　Finally, we note that the information retrieval field changes daily. For the most up to date coverage of the field, the
　　best sources include journals like the A CM Transactions on Information Systems, the Journal of the American Society for
　　Information Science and Technology, Information Processing and Management, and Information Retrieval. Other relevant papers
　　are found in the various information retrieval conferences such as ACM SIGIR www.sigir.org, NIST TREC trec.nist.gov, and the
　　ACM CIKM www.cikm.org. ...