A Contextualized and Personalized Approach for Mobile Search

Feng Gui, M. Adjouadi, N. Rishe
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引用次数: 17

Abstract

Mobile search is becoming increasingly important for mobile users as mobile devices are more widely used. Mobile search differs from standard PC-based web search in a number of ways: (1) the user interfaces and I/O are limited by screen real estate and tiny key pads are tiny, (2) limited bandwidth and costly connection time, (3) increased local search due to mobility. These limitations result in more navigational queries in the mobile search. Furthermore, user location, activities, preferences, and interaction history can also improve accuracy in determining relevance for mobile search. In the past, most personalized search algorithms are studied in the context of PC-based web search. Personalized mobile search should however play a bigger role at improving the user experiences. This paper focuses on the personalization strategies which explicitly and implicitly infer user search context from user current environment. We propose an architecture which collects user information (at mobile device and carrier network) and derives user intention in given situations. We show that personalized mobile search perform well for ambiguous queries and localized searches.
移动搜索的情境化和个性化方法
随着移动设备的广泛使用,移动搜索对移动用户来说变得越来越重要。移动搜索与标准的基于pc的web搜索在许多方面不同:(1)用户界面和I/O受到屏幕实际空间的限制,微小的键盘很小;(2)有限的带宽和昂贵的连接时间;(3)由于移动性增加了本地搜索。这些限制导致在移动搜索中出现更多的导航查询。此外,用户位置、活动、偏好和交互历史也可以提高确定移动搜索相关性的准确性。过去,大多数个性化搜索算法都是在基于pc的web搜索环境下进行研究的。个性化的移动搜索应该在改善用户体验方面发挥更大的作用。本文重点研究了从用户当前环境中显式和隐式推断用户搜索上下文的个性化策略。我们提出了一种收集用户信息(移动设备和运营商网络)并在给定情况下导出用户意图的架构。我们表明,个性化移动搜索在歧义查询和本地化搜索中表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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