TY - JOUR AU - Bader, Judith L AU - Theofanos, Mary Frances PY - 2003 DA - 2003/12/11 TI -在互联网上搜索癌症信息:分析自然语言搜索查询JO - J Med Internet Res SP - e31 VL - 5 IS - 4kw -癌症KW -互联网KW -搜索引擎KW -自然语言处理AB -背景:搜索健康信息是互联网用户最常见的任务之一。许多用户开始在流行的搜索引擎上搜索，而不是在著名的健康信息网站上搜索。我们知道，许多访问我们(国家癌症研究所)网站Cancer .gov的访问者都是通过搜索引擎结果中的链接到达的。目的:为了更多地了解我们的普通公众用户的具体需求，我们想了解普通用户真正想知道的关于癌症的信息，他们是如何表达他们的问题的，以及他们使用了多少细节。方法:美国国家癌症研究所与AskJeeves公司合作开发了一种方法，用于捕获、采样和分析Ask.com网站3个月来与癌症相关的查询，Ask.com是美国著名的消费者搜索引擎，每周收到超过3500万次查询。使用国家癌症研究所提供的500个术语和词根的基准集，AskJeeves确定了2001年8月为期一周的癌症查询测试样本。在这500个词条中，只有37个在17208个查询中出现≥5次/天。使用这37个术语，在2001年6月至8月的实际测试期间，在Ask.com查询日志中发现了204165个癌症查询实例。其中，7500个个人用户问题被随机选择进行详细分析，并分配到适当的类别。给出了样本查询的确切语言。 Results: Considering multiples of the same questions, the sample of 7500 individual user queries represented 76077 queries (37% of the total 3-month pool). Overall 78.37% of sampled Cancer queries asked about 14 specific cancer types. Within each cancer type, queries were sorted into appropriate subcategories including at least the following: General Information, Symptoms, Diagnosis and Testing, Treatment, Statistics, Definition, and Cause/Risk/Link. The most-common specific cancer types mentioned in queries were Digestive/Gastrointestinal/Bowel (15.0%), Breast (11.7%), Skin (11.3%), and Genitourinary (10.5%). Additional subcategories of queries about specific cancer types varied, depending on user input. Queries that were not specific to a cancer type were also tracked and categorized. Conclusions: Natural-language searching affords users the opportunity to fully express their information needs and can aid users naïve to the content and vocabulary. The specific queries analyzed for this study reflect news and research studies reported during the study dates and would surely change with different study dates. Analyzing queries from search engines represents one way of knowing what kinds of content to provide to users of a given Web site. Users ask questions using whole sentences and keywords, often misspelling words. Providing the option for natural-language searching does not obviate the need for good information architecture, usability engineering, and user testing in order to optimize user experience. SN - 1438-8871 UR - //www.mybigtv.com/2003/4/e31/ UR - https://doi.org/10.2196/jmir.5.4.e31 UR - http://www.ncbi.nlm.nih.gov/pubmed/14713659 DO - 10.2196/jmir.5.4.e31 ID - info:doi/10.2196/jmir.5.4.e31 ER -