Proven portals best practices for planning, designing, and developing enterprise portals
Bibliographic record
Abstract
Praise for Proven Portals“Enterprise portals are a key component in supporting enterprise business integration, and this book is a must-read for anyone involved in planning or deploying a portal solution.”i¾ i¾ i¾ i¾ i¾ -Colin White, President, Intelligent Business Strategies“Enterprise portals have moved from the fringes of business to a core competency in the span of a few short years. This book provides the balanced overview managers need to make intelligent decisions without dragging them into a morass of technical detail.”i¾ i¾ i¾ i¾ i¾ -Marcia Robinson, President, E-Business Strategies i¾ i¾ i¾ i¾ i¾ i¾ i¾ i¾ i¾ Author of Services Blueprint: Roadmap for Execution“Portals have become the ubiquitous format for most uses of the Web. If you are venturing into portal land, whether for the first time or after a few experiences, Dan Sullivan's book, Proven Portals: Best Practices for Planning, Designing, and Developing Enterprise Portals, is a valuable guide for getting organized and oriented. Understanding the approaches, technologies, and best practices described in this book will help ensure that your portal project is both a technical and a business success.”i¾ i¾ i¾ i¾ i¾ -Rose O'Donnell, Vice President of Engineering, Bowstreet, Inc.This book is chock-full of valuable knowledge and practical advice on implementing portals. Dan Sullivan once again gives us comprehensive information and useful techniques for delivering what's become a business staple. A must-read for practitioners and managers alike! --Jill Dyche, Partner, Baseline Consulting GroupIncreasingly, corporations are turning to portals to foster more integrated, Web-based user experiences for employees, customers, and vendors. By providing collaborative, personalized environments and adaptive workspaces, portals allow businesses to better acquire, serve, and retain customers; more effectively manage production and sales; and empower their staff with instant access to critical information. Focusing on critical elements of portal implementations, Proven Portals combines design principles with a series of in-depth case studies exploring how innovative enterprises, from NASA and Johnson Controls to CARE Canada and Empire Blue Cross Blue Shield, have successfully deployed portal technologies to reap significant rewards.In this book the author shares proven strategies for: Organizing information in an intuitive, coherent manner Creating a modular, adaptable framework for application integration Developing a robust, scalable architecture Improving search and navigation Implementing collaboration and content managementFilled with best practices developed by leading organizations and portal designers, this book provides practical advice for: Leveraging portals to better serve customers Delivering business intelligence across the organization Deploying effective knowledge management systems Ensuring adoption by end users Measuring a portal's return on investmentPortals are revolutionizing the way businesses handle e-commerce, customer relationships, and business intelligence. Proven Portals gives IT managers the foundation they need to plan, design, and develop enterprise portals for maximum customer satisfaction, improved analytics on demand, and more rigorous knowledge management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.020 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".