Retrieving Knowledge
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Extracting Knowledge From Opinion Mining
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.
Powerful Teaching
Author: Pooja K. Agarwal
language: en
Publisher: John Wiley & Sons
Release Date: 2024-11-13
Unleash powerful teaching and the science of learning in your classroom Powerful Teaching: Unleash the Science of Learning empowers educators to harness rigorous research on how students learn and unleash it in their classrooms. In this book, cognitive scientist Pooja K. Agarwal, Ph.D., and veteran K–12 teacher Patrice M. Bain, Ed.S., decipher cognitive science research and illustrate ways to successfully apply the science of learning in classrooms settings. This practical resource is filled with evidence-based strategies that are easily implemented in less than a minute—without additional prepping, grading, or funding! Research demonstrates that these powerful strategies raise student achievement by a letter grade or more; boost learning for diverse students, grade levels, and subject areas; and enhance students’ higher order learning and transfer of knowledge beyond the classroom. Drawing on a fifteen-year scientist-teacher collaboration, more than 100 years of research on learning, and rich experiences from educators in K–12 and higher education, the authors present highly accessible step-by-step guidance on how to transform teaching with four essential strategies: Retrieval practice, spacing, interleaving, and feedback-driven metacognition. With Powerful Teaching, you will: Develop a deep understanding of powerful teaching strategies based on the science of learning Gain insight from real-world examples of how evidence-based strategies are being implemented in a variety of academic settings Think critically about your current teaching practices from a research-based perspective Develop tools to share the science of learning with students and parents, ensuring success inside and outside the classroom Powerful Teaching: Unleash the Science of Learning is an indispensable resource for educators who want to take their instruction to the next level. Equipped with scientific knowledge and evidence-based tools, turn your teaching into powerful teaching and unleash student learning in your classroom.
Knowledge-Based Information Retrieval and Filtering from the Web
Author: Witold Abramowicz
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-03-09
Knowledge-Based Information Retrieval and Filtering from the Web contains fifteen chapters, contributed by leading international researchers, addressing the matter of information retrieval, filtering and management of the information on the Internet. The research presented deals with the need to find proper solutions for the description of the information found on the Internet, the description of the information consumers need, the algorithms for retrieving documents (and indirectly, the information embedded in them), and the presentation of the information found. The chapters include: -Ontological representation of knowledge on the WWW; -Information extraction; -Information retrieval and administration of distributed documents; -Hard and soft modeling based knowledge capture; -Summarization of texts found on the WWW; -User profiles and personalization for web-based information retrieval system; -Information retrieval under constricted bandwidth; -Multilingual WWW; -Generic hierarchical classification using the single-link clustering; -Clustering of documents on the basis of text fuzzy similarity; -Intelligent agents for document categorization and adaptive filtering; -Multimedia retrieval and data mining for E-commerce and E-business; -A Web-based approach to competitive intelligence; -Learning ontologies for domain-specific information retrieval; -An open, decentralized architecture for searching for, and publishing information in distributed systems.