Journal article Open Access

WevQuery: Testing Hypotheses about Web Interaction Patterns

Aitor Apaolaza; Markel Vigo

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  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  "description": "<p>Remotely stored user interaction logs, which give access to a wealth of data generated by large numbers of users, have been long used to understand if interactive systems meet the expectations of designers. Unfortunately, detailed insight into users&#39; interaction behaviour still requires a high degree of expertise and domain specific knowledge. We present WevQuery, a scalable system to query user interaction logs in order to allow designers to test their hypotheses about users&#39; behaviour. WevQuery supports this purpose using a graphical notation to define the interaction patterns designers are seeking. WevQuery is scalable as the queries can then be executed against large user interaction datasets by employing the MapReduce paradigm. This way WevQuery provides designers effortless access to harvest users&#39; interaction patterns, removing the burden of low-level interaction data analysis. We present two scenarios to showcase the potential of WevQuery, from the design of the queries to their execution on real interaction data accounting for 5.7m events generated by 2,445 unique users.</p>", 
  "license": "", 
  "creator": [
      "affiliation": "University of Manchester", 
      "@type": "Person", 
      "name": "Aitor Apaolaza"
      "affiliation": "University of Manchester", 
      "@type": "Person", 
      "name": "Markel Vigo"
  "headline": "WevQuery: Testing Hypotheses about Web Interaction Patterns", 
  "image": "", 
  "datePublished": "2017-06-30", 
  "url": "", 
  "keywords": [
    "Hypothesis Testing", 
    "A/B Testing", 
    "User Interface Evaluation", 
  "@context": "", 
  "identifier": "", 
  "@id": "", 
  "@type": "ScholarlyArticle", 
  "name": "WevQuery: Testing Hypotheses about Web Interaction Patterns"
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