Research the goals of people using search
Daniel E. Rose, who worked at AltaVista and Yahoo, explored the goals of users who encourage them to search the search engines. Together with Danny Levinson (Danny Levinson) in the theses Understanding User Goals in Web Search, he described the research process and results.
To begin with, based on the AltaVista search query log, a classification of user goals was developed. All requests (except for specific ones) should fall into any of these categories:
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Rose says that search engines should take into account the true goals that guide their users, and accordingly improve their interface. Unfortunately, it is difficult to identify these targets automatically.
Under the cut a brief description of the further work of Rose and Levinson. The full version of their theses and other articles on people's behavior and search are on my site.
To take the first steps, the authors developed a special tool for manual classification of requests. They analyzed about 500 randomly selected English search phrases from AltaVista server logs and manually assigned each of them to a specific category. Here are the results:
It is interesting to note that 40% of requests were not informational at all, and most of the information requests were about finding a specific product or service, and not about finding out the facts about it. This is in contradiction with the purpose for which the search engines were originally created - the search for information in the “electronic library” even in the pre-Internet era. In fact, only 35% of requests matched this idea.
It is worth noting that keyword samples were conducted in several stages at different times and seasons. The distribution of results in all cases was similar.
Unfortunately, the authors do not give any practical recommendations on the application of these results. They say that they have created a framework, a framework through which further research can be conducted in order to improve the performance of search engines. Rose and Levinson offer readers to try this framework, develop its ideas and highlight the practical benefits for themselves.
To begin with, based on the AltaVista search query log, a classification of user goals was developed. All requests (except for specific ones) should fall into any of these categories:
')
Rose says that search engines should take into account the true goals that guide their users, and accordingly improve their interface. Unfortunately, it is difficult to identify these targets automatically.
Under the cut a brief description of the further work of Rose and Levinson. The full version of their theses and other articles on people's behavior and search are on my site.
To take the first steps, the authors developed a special tool for manual classification of requests. They analyzed about 500 randomly selected English search phrases from AltaVista server logs and manually assigned each of them to a specific category. Here are the results:
It is interesting to note that 40% of requests were not informational at all, and most of the information requests were about finding a specific product or service, and not about finding out the facts about it. This is in contradiction with the purpose for which the search engines were originally created - the search for information in the “electronic library” even in the pre-Internet era. In fact, only 35% of requests matched this idea.
It is worth noting that keyword samples were conducted in several stages at different times and seasons. The distribution of results in all cases was similar.
Unfortunately, the authors do not give any practical recommendations on the application of these results. They say that they have created a framework, a framework through which further research can be conducted in order to improve the performance of search engines. Rose and Levinson offer readers to try this framework, develop its ideas and highlight the practical benefits for themselves.
Source: https://habr.com/ru/post/56732/
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