Opinion Mining in Information Retrieval, Bhatia Surbhi, Chaudhary Poonam, Dey Nilanjan
Автор: Miroslav Bursa et al Название: Information Technology in Bio- and Medical Informatics ISBN: 3319642642 ISBN-13(EAN): 9783319642642 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 8th International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2017, held in Lyon, France, in August 2017. The 3 revised full papers and 6 poster papers presented were carefully reviewed and selected from 15 submissions.
Описание: Explores new developments in the field of information and communication technologies and explores how complex information systems interact with and affect one another, woven into the fabric of an information-rich world. This handbook includes coverage of customer experience management, information systems planning, cellular networking, public policy development, and knowledge governance.
Автор: Muhammad Sarfraz Название: Critical Approaches to Information Retrieval Research ISBN: 1799810216 ISBN-13(EAN): 9781799810216 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 26195.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Information retrieval (IR) is considered to be the science of searching for information from a variety of information sources related to texts, images, sounds, or multimedia. With the rise of the internet and digital databases, updated information retrieval methodologies are essential to ensure the continued facilitation and enhancement of information exchange.
Critical Approaches to Information Retrieval Research is a critical scholarly publication that provides multidisciplinary examinations of theoretical innovations and methods in information retrieval technologies including search and storage applications for data, text, image, sound, document, and video retrieval. Featuring a wide range of topics including data mining, machine learning, and ontology, this book is ideal for librarians, software engineers, data scientists, professionals, researchers, information engineers, scientists, practitioners, and academicians working in the fields of computer science, information technology, information and communication sciences, education, health, library, and more.
Автор: Muhammad Sarfraz Название: Critical Approaches to Information Retrieval Research ISBN: 1799810224 ISBN-13(EAN): 9781799810223 Издательство: Mare Nostrum (Eurospan) Цена: 22037.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Information retrieval (IR) is considered to be the science of searching for information from a variety of information sources related to texts, images, sounds, or multimedia. With the rise of the internet and digital databases, updated information retrieval methodologies are essential to ensure the continued facilitation and enhancement of information exchange. Critical Approaches to Information Retrieval Research is a critical scholarly publication that provides multidisciplinary examinations of theoretical innovations and methods in information retrieval technologies including search and storage applications for data, text, image, sound, document, and video retrieval. Featuring a wide range of topics including data mining, machine learning, and ontology, this book is ideal for librarians, software engineers, data scientists, professionals, researchers, information engineers, scientists, practitioners, and academicians working in the fields of computer science, information technology, information and communication sciences, education, health, library, and more.
Автор: Rashmi Agrawal, Neha Gupta Название: Extracting Knowledge From Opinion Mining ISBN: 152256117X ISBN-13(EAN): 9781522561170 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 32848.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data mining techniques are commonly used to extract meaningful information from the web, such as data from web documents, website usage logs, and hyperlinks. Building on this, modern organizations are focusing on running and improving their business methods and returns by using opinion mining.Extracting Knowledge From Opinion Mining is an essential resource that presents detailed information on web mining, business intelligence through opinion mining, and how to effectively use knowledge retrieved through mining operations. While highlighting relevant topics, including the differences between ontology-based opinion mining and feature-based opinion mining, this book is an ideal reference source for information technology professionals within research or business settings, graduate and post-graduate students, as well as scholars.
Автор: Gunter Wallner Название: Data Analytics Applications in Gaming and Entertainment ISBN: 1138104434 ISBN-13(EAN): 9781138104433 Издательство: Taylor&Francis Рейтинг: Цена: 16078.00 р. Наличие на складе: Поставка под заказ.
Описание: Over the last decade big data and data mining has received growing interest and importance in game production to process and draw actionable insights from large volumes of player-related data in order to inform game design, to ensure customer satisfaction, to maximize revenues, and to drive technical innovation.
Описание: Presents the latest advances in multidisciplinary research methods and applications and examines effective techniques for managing and utilizing information resources. This book features extensive coverage across a range of relevant perspectives and topics, such as knowledge discovery, spatial indexing, and data mining.
Автор: Binxing Fang, Yan Jia Название: Groups and Interaction ISBN: 3110597772 ISBN-13(EAN): 9783110597776 Издательство: Walter de Gruyter Рейтинг: Цена: 16169.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The three volume set provides a systematic overview of theories and technique on social network analysis.Volume 2 of the set mainly focuses on the formation and interaction of group behaviors. Users’ behavior analysis, sentiment analysis, influence analysis and collective aggregation are discussed in detail as well. It is an essential reference for scientist and professionals in computer science.
Автор: Chao Zhang, Jiawei Han Название: Multidimensional Mining of Massive Text Data ISBN: 1681735210 ISBN-13(EAN): 9781681735214 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 14692.00 р. Наличие на складе: Нет в наличии.
Описание: Unstructured text, as one of the most important data forms, plays a crucial role in data-driven decision making in domains ranging from social networking and information retrieval to scientific research and healthcare informatics. In many emerging applications, people's information need from text data is becoming multidimensional—they demand useful insights along multiple aspects from a text corpus. However, acquiring such multidimensional knowledge from massive text data remains a challenging task. This book presents data mining techniques that turn unstructured text data into multidimensional knowledge. We investigate two core questions. (1) How does one identify task-relevant text data with declarative queries in multiple dimensions? (2) How does one distill knowledge from text data in a multidimensional space? To address the above questions, we develop a text cube framework. First, we develop a cube construction module that organizes unstructured data into a cube structure, by discovering latent multidimensional and multi-granular structure from the unstructured text corpus and allocating documents into the structure. Second, we develop a cube exploitation module that models multiple dimensions in the cube space, thereby distilling from user-selected data multidimensional knowledge. Together, these two modules constitute an integrated pipeline: leveraging the cube structure, users can perform multidimensional, multigranular data selection with declarative queries; and with cube exploitation algorithms, users can extract multidimensional patterns from the selected data for decision making. The proposed framework has two distinctive advantages when turning text data into multidimensional knowledge: flexibility and label-efficiency. First, it enables acquiring multidimensional knowledge flexibly, as the cube structure allows users to easily identify task-relevant data along multiple dimensions at varied granularities and further distill multidimensional knowledge. Second, the algorithms for cube construction and exploitation require little supervision; this makes the framework appealing for many applications where labeled data are expensive to obtain.
Описание: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining presents novel algorithms for academic search, recommendation and association rule mining that have been developed and optimized for different commercial as well as academic purpose systems. Along with the design and implementation of algorithms, a major part of the work presented in the book involves the development of new systems both for commercial as well as for academic use. In the first part of the book the author introduces a novel hierarchical heuristic scheme for re-ranking academic publications retrieved from standard digital libraries. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. In order to evaluate the performance of the introduced algorithms, a meta-search engine has been designed and developed that submits user queries to standard digital repositories of academic publications and re-ranks the top-n results using the introduced hierarchical heuristic scheme. In the second part of the book the design of novel recommendation algorithms with application in different types of e-commerce systems are described. The newly introduced algorithms are a part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. The initial version of the system uses a novel hybrid recommender (user, item and content based) and provides daily recommendations to all active subscribers of the provider (currently more than 30,000). The recommenders that we are presenting are hybrid by nature, using an ensemble configuration of different content, user as well as item-based recommenders in order to provide more accurate recommendation results.The final part of the book presents the design of a quantitative association rule mining algorithm. Quantitative association rules refer to a special type of association rules of the form that antecedent implies consequent consisting of a set of numerical or quantitative attributes. The introduced mining algorithm processes a specific number of user histories in order to generate a set of association rules with a minimally required support and confidence value. The generated rules show strong relationships that exist between the consequent and the antecedent of each rule, representing different items that have been consumed at specific price levels. This research book will be of appeal to researchers, graduate students, professionals, engineers and computer programmers.
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