Search Results for Debugging Relevance Issues Search

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1. [LUCID] Debugging Relevance Issues in Search

   . Debugging Relevance Issues Debugging relevance issues is much like Edison's genius equation : 1% inspiration and 99% perspiration. Debugging search systems is time consuming, yet necessary. It can be both frustrating and enjoyable within

   http://www.lucidimagination.com/Community/Hear-from-the-Experts/Articles/Debu...

2. [LUCID] Developing Search Applications With Solr - Detailed Course Schedule

   token filters; use of the admin analysis tool to see how the analysis stack created to tokenize content affects a query Findability: How configuration files and decisions will impact the findability and relevancy of your search results; filters used in the analysis stack and the direct impact on relevance of search results. Understanding Relevance Determining relevance quality, using scoring models, payloads, and debugging relevance issues How to use a query-time field boost to Improve relevance

   http://www.lucidimagination.com/solutions/services/training/detailed-course-s...

3. [LUCID] Optimizing Findability in Lucene and Solr

   . Learn more about possible relevance problems in your application in my article titled Debugging Relevance Issues in Search

   http://www.lucidimagination.com/Community/Hear-from-the-Experts/Articles/Opti...

4. [LUCID] Lucid Imagination Streamlines Apache Solr for Enterprise Search Applications

   assistance program for search application developers. LucidWorks Certified Distribution for Solr also includes Luke, a handy development and diagnostic tool that allows developers to examine and modify existing Lucene indexes, and quickly identify issues in data feed, search accuracy and search relevancy

   http://www.lucidimagination.com/About/Company-News/Lucid-Imagination-Streamli...

5. [LUCID] Interview with Walter Underwood of Netflix

   customer experience using autocomplete, improved findability and other techniques for over two million searches per day. Walter discusses migrating to Solr, configuring for known data search, intuiting user behavior from log files, tuning autocompletion, debugging space variants, faceted browsing, and

   http://www.lucidimagination.com/Community/Hear-from-the-Experts/Podcasts-and-...

6. [LUCID] Getting Started with Lucene

   needs. For instance, a user often has a deep understanding of their need, but a simple search box geared towards keyword entry is ill-equipped to deal with that need. On the flip side, users sometimes know only one or two vague terms and still expect highly relevant results. Your job, of course, is to

   http://www.lucidimagination.com/Community/Hear-from-the-Experts/Articles/Gett...

7. [LUCID] Scaling Lucene and Solr

   a very compact and powerful search library while Solr is an enterprise search engine built on top of the Lucene library. Lucene gives you killer information retrieval core technology in a compact package, and Solr builds out features on top, including: a platform independent interface, faceting, replication, caching, large scale distributed search, and much more. This article assumes you are familiar with the Lucene/Solr basics , but should be fairly accessible to those that are investigating the scalability of the Lucene Stack . Lucene and Solr are both highly scalable search solutions. Depending on a multitude of factors, a single machine can easily host a Lucene/Solr index of 5 – 80+ million documents, while a distributed

   http://www.lucidimagination.com/Community/Hear-from-the-Experts/Articles/Scal...

8. [LUCID] Interview with Doug Cutting

   never taken off. That’ s, as I said, the lament of IR that relevance feedback hasn't taken off despite everyone knowing that it’ s the best way to improve searches. Grant Ingersoll: Yeah; the thought of doing an extra query, especially an extra large

   http://www.lucidimagination.com/Community/Hear-from-the-Experts/Podcasts-and-...