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A List Apart: Articles: Testing Search for Relevancy and Precision
Despite the fact that site search often receives the most traffic, it’s also the place where the user experience designer bears the least influence. Few tools exist to appraise the quality of the search experience, much less strategize ways to improve it. When it comes to site search, user experience designers are often sidelined like the single person at an old flame’s wedding: Everything seems to be moving along without you, and if you slipped out halfway through, chances are no one would notice. But relevancy testing and precision testing offer hope. These are two tools you can use to analyze and improve the search user experience.
A List Apart: Articles: Internal Site Search Analysis: Simple, Effective, Life Altering!
Understanding of your site visitors’ intent is one of the most delightful parts of web data analysis. In this article, we’ll learn five ways to analyze your internal site-search data—data that’s easy to get, to understand, and to act on.
But let’s take a step back. Why should you care about this in the first place? Good question.
In the good old days, people dutifully used site navigation at the left, right, or top of a website. But, two websites have fundamentally altered how we navigate the web: Amazon, because the site is so big, sells so many things, and is so complicated that many of us go directly to the site search box on arrival. And Google, which has trained us to show up, type what we want, and hit the search button.
A List Apart: Articles: Beyond Goals: Site Search Analytics from the Bottom Up
Avinash Kaushik demonstrated that site search analytics (SSA) is a powerful tool you can use to assess customer intent quantitatively. In SSA, as with all flavors of web analytics (WA), you can work from the top-down; by starting with clear, measurable metrics based on your organization’s goals, you can benchmark and continually optimize the performance of your content and designs. While goal-driven analysis is wonderfully useful, we’ll explore a different, “bottom-up” approach that relies on pattern analysis and failure analysis to help you understand your users’ intent in qualitative ways that complement the top-down approach.
Read It: Search User Interfaces
"Search is an integral part of peoples' online lives; people turn to search engines for help with a wide range of needs and desires, from satisfying idle curiousity to finding life-saving health remedies, from learning about medieval art history to finding video game solutions and pop music lyrics. Web search engines are now the second most frequently used online computer application, after email. Not long ago, most software applications did not contain a search module. Today, search is fully integrated into operating systems and is viewed as an essential part of most information systems." (Marti A. Hearst
Collection: Search Patterns
A sandbox for collecting search examples, patterns, and anti-patterns.
Please add tags, notes, and comments, and suggest new examples.
Over time, I hope to add patterns that illustrate user behavior and the information architecture of search.
I'll be blogging about patterns at findability.org/, there's a slidecast, and I'm writing a book on the topic.
Choosing the Right Search Results Page Layout: Make the Most of Your Width :: UXmatters
Page layout forms the foundation in presenting search results. Your layout decisions for search results pages will have tremendous impact on the user experience for your entire site. Choosing the right width for search results is important, and the optimal width for search results may be a great deal narrower than some people using big monitors would believe.
Starting from Zero: Winning Strategies for No Search Results Pages :: UXmatters
Search results pages are some of the most visited pages on typical e-commerce sites—to say nothing of a search engine like Google. Many articles appear each year about optimal search algorithms, database performance, and the like. In contrast, very few publications focus on improving the search experience from the customer’s perspective.
Optimizing for Hunters Part 2: Beyond Search and Navigation | Get Elastic
To follow up our recent post on customer motivation and optimizing your website for hunters (e.g. moms armed with Christmas lists), I want to show you some examples beyond the search box and navigation menu.
I’ll use a personal story - I’m in the market for a car GPS. Previously knowing nothing about them (features, brands, prices etc), so I started off a howser. I decided I want to check Crutchfield (great product filters and product descriptions), Amazon (access to more products, the seller marketplace and more customer reviews) and Best Buy Canada (Canadian pricing, option to pick up in store).
World-Information Institute - Deep Search --> video's of the conference
With the explosion of information in all shades and languages, issues of orientation and navigation in the oceans of knowledge pose themselves with renewed urgency. Information is useless if it cannot be found and it is not a co-incidence that a search engine like Google turned into one of the most significant companies of the new century. There is an intense debate in science and industry on the implications of these global trends, but there is also a growing awareness as to the socio-cultural implications of "search" and the information retrieval of the future.
Drupal Code Search
Drupal Code Search helps you find Drupal code easier!
* Search source code from thousands of Drupal modules and themes.
* Use the power of regular expressions to find exactly what you need.
* Easily restrict results to specific Drupal versions and programming languages.
* Results provided by the Google Code Search API.
Drupal with millions of nodes - Wesley Tanaka
Drupal 6 has a few problems with large numbers of nodes.
Slow query problems in search index update (/cron.php)
There are two slow queries in the search index update process that gets run during cron. Slow query #1, in node_update_index(), picks out the node IDs to (re)index. Slow query #2, in search_update_totals(), figures out which rows have been deleted from {search_index} and need to be deleted from {search_total}.
Zend Lucene Search - part1 - creating index | Ganesh H S
In this article i will be discussing about creating index using zend lucene search .
Conventionally most of the site search are powered by database driven.
Lets consider my blog site, if anyone comes to my site and wants to search for any keyword, if i have to give search results i may have to look into articles table, comments table, executing SQL queries against 2 tables is acceptable, but if we go to any e-commerce application, we may have to search against lot of categories and products, since database queries are costlier, it consumes more resources. One more important point is we cannot get more relevant results first, in general we cannot rank the search results.
Apache Lucene is a high-performance, full-featured text search engine library written entirely in Java. This is being used in most of web2.0 websites. Zend_Search_Lucene was derived from the Apache Lucene project.
A Stemming Analyzer for Zend’s PHP Lucene
. One of the roadblocks to implementing a Google-like search, however, was the absence of a stemming analyzer in the Zend package.
While using PHP Lucene, I came across this issue while developing a plug-in for wordpress. I wasn’t getting the relevancy I needed in test searches that I was looking for, and I decided to develop one of my own.
12.3. Het doorzoeken van een index
Er zijn twee manieren om door een index te zoeken. De eerste methode gebruikt de Query Parser om een query op te bouwen van een string. De tweede bied de mogelijkheid je eigen queries te maken via de Zend_Search_Lucene API.
A word on Lucene’s PHP port by Zend
Lucene is an open source search engine written in Java. If you have never heard of it prior to now, listen to this: It allows you to create a mini google-like search for anything. That’s right — anything.
Page 7: Querying Our Index - Creating A Fulltext Search Engine In PHP 5 With The Zend Framework's Zend Search Lucene - PHP articles and PHP tutorials - PHP 5, MySQL, PostgreSQL, AJAX, Web 2.0
On the previous page we looked at how to write queries to search the index. We learned how to include and exclude terms, and also how to search different fields in our indexed data.
Now we will look at actually pulling documents from our index using that term.
Using Zend Search Lucene in a symfony app at Spindrop
If you’re like me you’ve probably followed the Askeet tutorial on Search in order to create a decent search engine for your web app. It’s fairly straight forward, but they hinted that when Zend Search Lucene (ZSL) is released, that might be the way to go. Well we are in luck, ZSL is available, so let’s just dive right in.
The Lucene Search Index and symfony at Spindrop
This article is meant to followup sfZendPlugin where we learn a newer way of obtaining the Zend Framework.
In this tutorial we’re going to delve into the Lucene index. Zend Search Lucene relies on building a Lucene index. This is a directory that contains files that can be indexed and queried by Lucene or other ports. In our example we’ll be creating a search for user profiles.
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