Data warehouse

This book constitutes the refereed proceedings of the 13th International Conference of the CLEF Association, CLEF 2022, held in Bologna, Italy in September 2022.The conference has a clear focus on experimental information retrieval with special attention to the challenges of multimodality, multilinguality, and interactive search ranging from unstructured to semi structures and structured data.The 7 full papers presented together with 3 short papers in this volume were carefully reviewed and selected from 14 submissions. This year, the contributions addressed the following challenges: authorship attribution, fake news detection and news tracking, noise-detection in automatically transferred relevance judgments, impact of online education on children's conversational search behavior, analysis of multi-modal social media content, knowledge graphs for sensitivity identification, a fusion of deep learning and logic rules for sentiment analysis, medical concept normalization and domain-specific information extraction.In addition to this, the volume presents 7 "e;best of the labs"e; papers which were reviewed as full paper submissions with the same review criteria. 14 lab overview papers were accepted and represent scientific challenges based on new datasets and real world problems in multimodal and multilingual information access.

The low cost of getting started with cloud services can easily evolve into a significant expense down the road. That's challenging for teams developing data pipelines, particularly when rapid changes in technology and workload require a constant cycle of redesign. How do you deliver scalable, highly available products while keeping costs in check? With this practical guide, author Sev Leonard provides a holistic approach to designing scalable data pipelines in the cloud. Intermediate data engineers, software developers, and architects will learn how to navigate cost/performance trade-offs and how to choose and configure compute and storage. You'll also pick up best practices for code development, testing, and monitoring. By focusing on the entire design process, you'll be able to deliver cost-effective, high-quality products. This book helps you: Reduce cloud spend with lower cost cloud service offerings and smart design strategies Minimize waste without sacrificing performance by rightsizing compute resources Drive pipeline evolution, head off performance issues, and quickly debug with effective monitoring Set up development and test environments that minimize cloud service dependencies Create data pipeline code bases that are testable and extensible, fostering rapid development and evolution Improve data quality and pipeline operation through validation and testing

Peer-to-peer(P2P)computingiscurrentlyattractingenormousmediaattention, spurred by the popularity of ?le sharing systems such as Napster, Gnutella and Morpheus. In P2P systems a very large number of autonomous computing nodes (the peers) pool together their resources and rely on each other for data and services. The wealth of business opportunities promised by P2P networks has gene- ted much industrial interest recently, and has resulted in the creation of various industrial projects, startup companies, and special interest groups. Researchers from distributed computing, networks, agents and databases have also become excited about the P2P vision, and papers tackling open problems in this area have started appearing in high-quality conferences and workshops. Much of the recent research on P2P systems seems to be carried out by - search groups with a primary interest in distributed computation and networks. This workshop concentrated on the impact that current database research can have on P2P computing and vice versa. Although researchers in distributed data structures and databases have been working on related issues for a long time, the developed techniques are simply not adequate for the new paradigm.

The Information Management Systems group at the University of Padua, led by Maristella Agosti, has been a major contributor to information retrieval and digital libraries for nearly twenty years.This group has produced some of Italy's best-known IR researchers, whose work spans a broad range of topics, as the papers in this book demonstrate. One of the goalsof the IR book series is to highlight the work of academic research centers in our ?eld, in order to balancetheperceptionthateveryoneinIRworksforasearchenginecompany. One of the best aspects of our ?eld is that, as academic researchers, we can work with new graduate students and collaborate with companies to ensure that our research has direct impact on systems that people use every day. The Padua group is typical in this respect, and has been involved in a series of collaborations and major European projects over the years. I hope this volume inspires graduate students to pursue research in IR, and I encourage other research groups to contribute their own collections of papers. Amherst, Massachusetts. July 2007. W. Bruce Croft Preface The Information Management Systems (IMS) Research Group was formed in the Department of Information Engineering (formerly Department of El- tronicsandComputer Science)ofthe UniversityofPadua,Italy,in1987when the department was established. The group activities are concerned with the design,modelingandimplementationofadvancedinformationretrievaltools- such as search engines - and digital library systems.

The area of similarity searching is a very hot topic for both research and c- mercial applications. Current data processing applications use data with c- siderably less structure and much less precise queries than traditional database systems. Examples are multimedia data like images or videos that offer query by example search, product catalogs that provide users with preference based search, scientific data records from observations or experimental analyses such as biochemical and medical data, or XML documents that come from hetero- neous data sources on the Web or in intranets and thus does not exhibit a global schema. Such data can neither be ordered in a canonical manner nor meani- fully searched by precise database queries that would return exact matches. This novel situation is what has given rise to similarity searching, also - ferred to as content based or similarity retrieval. The most general approach to similarity search, still allowing construction of index structures, is modeled in metric space. In this book. Prof. Zezula and his co authors provide the first monograph on this topic, describing its theoretical background as well as the practical search tools of this innovative technology.