PDF Download Relevant Search: With applications for Solr and Elasticsearch
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Relevant Search: With applications for Solr and Elasticsearch
PDF Download Relevant Search: With applications for Solr and Elasticsearch
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About the Author
Doug Turnbull is a search relevance consultant at OpenSource Connections where he frequently speaks and blogs. Using Solr and Elasticsearch, Doug builds relevant, semantically enriched search experiences for clients across multiple domains.John Berryman is a data scientist at EventBrite where he specializes in recommendations and search. He is interested in the potential of integrating semantic understanding into search and discovery applications.
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Product details
Paperback: 360 pages
Publisher: Manning Publications; 1 edition (July 9, 2016)
Language: English
ISBN-10: 161729277X
ISBN-13: 978-1617292774
Product Dimensions:
7.5 x 0.5 x 10 inches
Shipping Weight: 1.8 pounds (View shipping rates and policies)
Average Customer Review:
4.4 out of 5 stars
13 customer reviews
Amazon Best Sellers Rank:
#224,445 in Books (See Top 100 in Books)
Although the book does create and environment abundant of useful knowledge pertaining to relevance problems within the search domain, it falls short in the majority of chapters by focusing too much on the organizational benefits of focusing on search relevance rather than on the applied problems that it tries to solve. I feel like the book would have been a better read had it been condensed to a thoughtfully organized 5 chapters instead of the broad stroked attempt at encompassing all things related to relevance. A majority of the readers will choose this book in order to unlock the potential that Elasticsearch and Solr have for modeling relevance within a search application. To that endeavor, this book excels in many ways. Its description of signals within documents and the emphasis on correct tokenization and analysis before indexing are great lingo and concepts to have when taking on the role of a search engineer. The examples and explanations are great and the authors do a good job of highlighting the importance of debugging relevance problems with the features available in the technologies used. As far as the concepts presented regarding how to build queries that run against an index engineered with relevance in mind I was enthralled by the content presented. And although the book was at times verbose and riddled with fluff pieces meant to sound joking and entertaining, they were mostly passable and one could still enjoy the thoughtfulness of the examples and code presented. However, at the end of the book, the content became increasingly unrelated and unfocused. The last 3 chapters could all be condensed into one "putting it all together" chapter. Not only that but the mention of the iterative cycle of relevance and collaborative filtering feel completely out of place within the intended goal of the book. The mentions of machine learning are appropriate but feel incredibly "hand-wavy" and some of the writing feels like it lacks depth. The organization of the book could have benefited from a larger and deeper focus on "term-centric" vs "field-centric" queries and the features available in the search engine to support those types of searches. Although the book is a decent introduction to the field I feel like it loses its focus at times and the end of it is a total miscalculation on it's target audience.
I expected more technical depth in how to build complex queries and understand what Lucene is doing with those queries "under the hood". This book barely touched on that, only briefly discussing indices, distributed computing and doc values, and not going into say how queries are compiled (are they even compiled? I don't know after reading this book). I also expected some discussion on how to combine several different types of rankings. I didn't really get that either, since the authors kind of stop after discussing how to combine 2 or 3 factors in simplistic ways. If you need to use lots of advanced function scores, scripted scores, and nested document types, this probably won't be more helpful than stack overflow. As a basic primer, it is a bit better than the elasticsearch intro book, though that is free online.
Really well written
Great book
An excellent book which weaves the process of building a great search application with the tools available to do so.
Very informative book about Search Technology !
I found this book on the MEAP program (Manning Early Access Program) and avidly read it as the chapters were released. It was, for me, an incredibly timely and valuable book because I had just landed a job building SOLR search for the local branch of a large multinational corporation. Although I had SOLR experience in my previous position, it was unique in that the whole idea of "relevance" didn't really apply - but it applied in spades in my new gig.Relevant Search (the book) was the next step in my education about what search is "really" about - finding the relevant "things" the user really wants to see. NOT about matching certain words. The book made a huge, positive difference in the results I was able to produce for my new employer and if you're going to be playing around in the "Search" space, you owe it to yourself to get this book. Reading it and using the suggestions and approaches in the book made a huge difference in how I approached the work, as well as providing incredibly useful "patterns" for discussing the whole problem of Search and Relevancy with my Product Manager, my SME's and upper management. I received a number of compliments for my knowledge - much of which I owed to reading this book.This book is not about the nuts and bolts of installing and running SOLR or ElasticSearch -- it IS about the important concepts (and some useful tricks and traps) for building Relevancy into your search tools. You will learn how to build better searches (and there are some included examples of actual query syntax).Think of it this way:Search is really not what you are after in a search application. Relevancy IS what you want. Relevancy is about getting the search to produce results that thrill your users - because it appears to match their needs and expectations. It is easy to match every instance of the word "maverick"... What users want is an application that "knows" the difference between "Maverick" the car, "maverick" the wild stallion, and "Maverick" the iconoclastic, anti-establishment hero of that famous early 60's TV show.. THAT is relevance.If that matters to you, buy this book.
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