Creating a Software Company? 9 Decisions You Have to Make f

If programming languages were weapons f

Live Ships Map - AIS - Vessel Traffic and Positions - AIS Marine Traffic f

Geopolitikai játszma Ukrajnában f


Deconstructing E-Commerce Search: The 12 Query Types f

This is the first in a series of articles on e-commerce search that draw on findings from our recent search usability report and benchmark.

In this article we’ll introduce 12 types of search queries identified during our large-scale usability study of e-commerce search. While not exhaustive they reflect the main types of queries that users rely on when searching in an e-commerce context.

During the usability study, the test subjects were observed to rely heavily on e-commerce search queries that included a theme, feature, relation, or symptom – yet most of 19 tested sites had poor support for these query types. Even among the 50 e-commerce giants we’ve benchmarked the support for most query types is meager at best, as should be evident from the graph above.

These benchmark results reveal surprisingly dismal support for essential e-commerce search query types. For example, among the top 50 grossing US e-commerce sites:

  • 16% of the e-commerce sites do not support that users search by product names (which appear on the product page).
  • 18% handle phonetic misspellings so poorly that users will have to pass a spelling test to be presented with results (e.g. 0 results for “Kitchen Aid Artysan” when looking for the “KitchenAid Artisan” mixer).
  • 70% require users to search by the exact same product type jargon the site uses, failing to return relevant products for a search such as “blow dryer” if “hair dryer” is used on the site, or “multifunction printer” vs “all-in-one printer”.
  • 22% of the sites don’t support search queries for a color variation (despite the product searched for being available in multiple colors).
  • 60% don’t support thematic search queries such as “spring jacket” or “office chair”.
  • 84% don’t handle queries that specify a subjective qualifier, such as “cheap” or “high quality”.
  • 60% don’t support symbols and abbreviations, resulting in users missing out on perfectly relevant products if searching for inch when the site has used  or in.

In this article, we’ll go over each of 12 query types of e-commerce search – with plenty of query samples, tips on how to best support each query type, and examples from the test sessions.

Note: This is the longest article we’ve published to date – a cup of coffee is advised. You may also download the article as a PDF or ePub.

Gartner: A megoldás szállítók korszaka véget ért! f


Tron: Legacy Encom Boardroom Visualization f

TechEmpower Web Framework Performance Comparison f

Barabási Albert-László - Behálozva EP1


Game of Thrones Remix on NESKeytar » Laser Harp / Theremin Hero (Greig Stewart) f

Full explanation of the NESKeytar construction and it’s various features coming soon.
Yes, I know I misspelled “functional”. A complete lack of proof reading, woops :(

Most of the buttons are functional and can be remapped to different functions, as can the whammy bar. It also has an onboard arpeggio and drum sequencer.

The sound comes from the original RP2A03 chip in the NES, giving it that classic 8-bit sound. All of the available sound channels are utilised.

The software runs on a raspberry pi and is written in a language called Pure Data (pd). There are various modes including a midi controller mode as well as a standalone mode, which allows the whole instrument to be used with a battery pack.


Futurama 3d

The Refactoring Tales f

Welcome to The Refactoring Tales, a book that documents some of the refactorings and changes I’ve made in recent (and mostly real-life) projects. This book isn’t going to teach you about language constructs, conditionals, functions, or so on, but hopefully offer insight into how to take steps to make your code more readable and more importantly, maintainable.

Think of how much time you spend maintaining code, rather than being able to write code from scratch. Day to day, I’m not typically creating new projects, but I am maintaining, editing or refactoring existing projects. This book is just like that. Each chapter will start by looking at some existing code, and over the course of a few pages we will examine, dissect and then refactor the code into an improved alternative. Of course, the idea of code being “better” is largely subjective, but even if you don’t quite agree with every step I take, you should be able to see the overall benefits.

No more clientside spaghetti. Organizing your code. | Human JavaScript f

Code is as much about people as it is about computers. Sure, it’s run by computers, but it’s written by, maintained by, and ultimately created for people. People are not computers. We are not robots. We are unpredictable, flawed, and irrational. The same people with the same tools and instructions won’t produce the same output each time. We generally don’t like being alone and we don’t work well in isolation. In fact, in order to do our best work we need to work with other people. None of these traits are bad things, quite the opposite. They’re what makes us who we are, they make us, well… human. Yet, as developers it’s easy for us to get so focused on optimizing for technology that we forget to optimize for people.

You can read about JavaScript, the language, elsewhere. Its good parts, bad parts, and ugly parts are well documented. This is a book about a specific set of tools, patterns, and approaches that we feel are optimized for people. These approaches enable our team to quickly build and deliver high-quality JavaScript applications for humans.

Markov Chains f

Markov chains, named after Andrey Markov, are mathematical systems that hop from one “state” (a situation or set of values) to another. For example, if you made a Markov chain model of a baby’s behavior, you might include “playing,” “eating”, “sleeping,” and “crying” as states, which together with other behaviors could form a ‘state space’: a list of all possible states. In addition, on top of the state space, a Markov chain tells you the probabilitiy of hopping, or “transitioning,” from one state to any other state—-e.g., the chance that a baby currently playing will fall asleep in the next five minutes without crying first.

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