Predicting Information Retrieval Performance, Robert M. Losee

Автор: Robert M. Losee
Название: Predicting Information Retrieval Performance
ISBN: 1681734729 ISBN-13(EAN): 9781681734729
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 41580.00 T
Наличие на складе: Невозможна поставка.
Описание: Information Retrieval performance measures are usually retrospective in nature, representing the effectiveness of an experimental process. However, in the sciences, phenomena may be predicted, given parameter values of the system. After developing a measure that can be applied retrospectively or can be predicted, performance of a system using a single term can be predicted given several different types of probabilistic distributions. Information Retrieval performance can be predicted with multiple terms, where statistical dependence between terms exists and is understood. These predictive models may be applied to realistic problems, and then the results may be used to validate the accuracy of the methods used. The application of metadata or index labels can be used to determine whether or not these features should be used in particular cases. Linguistic information, such as part-of-speech tag information, can increase the discrimination value of existing terminology and can be studied predictively.This work provides methods for measuring performance that may be used predictively. Means of predicting these performance measures are provided, both for the simple case of a single term in the query and for multiple terms. Methods of applying these formulae are also suggested.

Автор: Manning, Christopher D. Raghavan, Prabhakar Schutz
Название: Introduction to information retrieval
ISBN: 0521865719 ISBN-13(EAN): 9780521865715
Издательство: Cambridge Academ
Рейтинг:
Цена: 60190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Class-tested and coherent, this textbook teaches information retrieval, including web search, text classification, and text clustering from basic concepts. Ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students. Slides and additional exercises are available for lecturers.

Автор: Marion J. Ball; J.G. King; Judith V. Douglas
Название: Performance Improvement Through Information Management
ISBN: 1461268001 ISBN-13(EAN): 9781461268000
Издательство: Springer
Рейтинг:
Цена: 93160.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Highlighting performance improvement and business strategies throughout various health care settings, this text focuses on business drivers and management mechanisms, explaining when, how, and why information technology solutions are of value.

Автор: Virginia Dressler
Название: Framing Privacy in Digital Collections with Ethical Decision Making
ISBN: 168173401X ISBN-13(EAN): 9781681734019
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 46200.00 T
Наличие на складе: Невозможна поставка.
Описание: As digital collections continue to grow, the underlying technologies to serve up content also continue to expand and develop. As such, new challenges are presented whichcontinue to test ethical ideologies in everyday environs of the practitioner. There are currently no solid guidelines or overarching codes of ethics to address such issues. The digitization of modern archival collections, in particular, presents interesting conundrums when factors of privacy are weighed and reviewed in both small and mass digitization initiatives. Ethical decision making needs to be present at the onset of project planning in digital projects of all sizes, and we also need to identify the role and responsibility of the practitioner to make more virtuous decisions on behalf of those with no voice or awareness of potential privacy breaches.In this book, notions of what constitutes private information are discussed, as is the potential presence of such information in both analog and digital collections. This book lays groundwork to introduce the topic of privacy within digital collections by providing some examples from documented real-world scenarios and making recommendations for future research.A discussion of the notion privacy as concept will be included, as well as some historical perspective (with perhaps one the most cited work on this topic, for example, Warren and Brandeis' ""Right to Privacy,"" 1890). Concepts from the The Right to Be Forgotten case in 2014 (Google Spain SL, Google Inc. v Agencia Española de Protección de Datos, Mario Costeja González) are discussed as to how some lessons may be drawn from the response in Europe and also how European data privacy laws have been applied. The European ideologies are contrasted with the Right to Free Speech in the First Amendment in the U.S., highlighting the complexities in setting guidelines and practices revolving around privacy issues when applied to real life scenarios. Two ethical theories are explored: Consequentialism and Deontological. Finally, ethical decision making models will also be applied to our framework of digital collections. Three case studies are presented to illustrate how privacy can be defined within digital collections in some real-world examples.

Автор: Xiang Ren, Jiawei Han
Название: Mining Structures of Factual Knowledge from Text: An Effort-Light Approach
ISBN: 1681733943 ISBN-13(EAN): 9781681733944
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 102570.00 T
Наличие на складе: Невозможна поставка.
Описание: The real-world data, though massive, is largely unstructured, in the form of natural-language text. It is challenging but highly desirable to mine structures from massive text data, without extensive human annotation and labeling. In this book, we investigate the principles and methodologies of mining structures of factual knowledge (e.g., entities and their relationships) from massive, unstructured text corpora.Departing from many existing structure extraction methods that have heavy reliance on human annotated data for model training, our effort-light approach leverages human-curated facts stored in external knowledge bases as distant supervision and exploits rich data redundancy in large text corpora for context understanding. This effort-light mining approach leads to a series of new principles and powerful methodologies for structuring text corpora, including (1) entity recognition, typing and synonym discovery, (2) entity relation extraction, and (3) open-domain attribute-value mining and information extraction. This book introduces this new research frontier and points out some promising research directions.

Автор: Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis
Название: Data Exploration Using Example-Based Methods
ISBN: 1681734575 ISBN-13(EAN): 9781681734576
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 87780.00 T
Наличие на складе: Невозможна поставка.
Описание: Data usually comes in a plethora of formats and dimensions, rendering the information extraction and exploration processes challenging. Thus, being able to perform exploratory analyses of the data with the intent of having an immediate glimpse of some of the data properties is becoming crucial. Exploratory analyses should be simple enough to avoid complicated declarative languages (such as SQL) and mechanisms, while at the same time retaining the flexibility and expressiveness of such languages. Recently, we have witnessed a rediscovery of the so-called example-based methods, in which the user, or analyst, circumvents query languages by using examples as input. An example is a representative of the intended results or, in other words, an item from the result set. Example-based methods exploit inherent characteristics of the data to infer the results that the user has in mind but may not be able to (easily) express. They can be useful in cases where a user is looking for information in an unfamiliar dataset, when they are performing a particularly challenging task like finding duplicate items, or when they are simply exploring the data. In this book, we present an excursus over the main methods for exploratory analysis, with a particular focus on example-based methods. We show how different data types require different techniques and present algorithms that are specifically designed for relational, textual, and graph data. The book also presents the challenges and new frontiers of machine learning in online settings that have recently attracted the attention of the database community. The book concludes with a vision for further research and applications in this area.

Автор: Tony McEnery; Chris Paice
Название: 14th Information Retrieval Colloquium
ISBN: 3540198083 ISBN-13(EAN): 9783540198086
Издательство: Springer
Рейтинг:
Цена: 81050.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A comprehensive overview of current research in the field of information retrieval, as well as indications of future developments. The text includes chapters on such topics as an intelligent multimodal interface for a materials information system, and hypermedia links and information retrieval.

Автор: Fabio Crestani; Gabriella Pasi
Название: Soft Computing in Information Retrieval
ISBN: 3790824739 ISBN-13(EAN): 9783790824735
Издательство: Springer
Рейтинг:
Цена: 153720.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Information retrieval (IR) aims at defining systems able to provide a fast and effective content-based access to a large amount of stored information. A promising direction to increase the effectiveness of IR is to model the concept of "partially intrinsic" in the IR process and to make the systems adaptive, i.e.

Автор: Lori McCay-Peet, Elaine G. Toms
Название: Researching Serendipity in Digital Information Environments
ISBN: 1681730936 ISBN-13(EAN): 9781681730936
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 46200.00 T
Наличие на складе: Невозможна поставка.
Описание: Brings together different disciplinary perspectives and examines the motivations for studying serendipity, the various ways in which serendipity has been approached in the research, methodological approaches to build theory, and how it may be facilitated.

Автор: Massimo Melucci; Ricardo Baeza-Yates
Название: Advanced Topics in Information Retrieval
ISBN: 3642268633 ISBN-13(EAN): 9783642268632
Издательство: Springer
Рейтинг:
Цена: 107130.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this book, the authors, selected from the lecturers of the European Summer School in Information Retrieval, illustrate key problems and topics in the current development of Information Retrieval and on future search engine technology.

Автор: Pennington Diane
Название: Social Tagging for Linking Data Across Environments
ISBN: 1783303387 ISBN-13(EAN): 9781783303380
Издательство: Facet
Рейтинг:
Цена: 109120.00 T
Наличие на складе: Нет в наличии.
Описание: This book, representing researchers and practitioners across different information professions, will explore how social tags can link content across a variety of environments.

Автор: Pavel Braslavski; Nikolay Karpov; Marcel Worring;
Название: Information Retrieval
ISBN: 3319254847 ISBN-13(EAN): 9783319254845
Издательство: Springer
Рейтинг:
Цена: 59630.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.