共查询到20条相似文献，搜索用时 15 毫秒
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[目的/意义] 针对当前我国网络用户的健康信息检索行为, 探索利用中文搜索引擎的健康信息检索规律, 为完善健康搜索引擎和网站建设提供参考。[方法/过程] 基于搜狗搜索引擎的大规模查询日志, 采用日志挖掘的方法, 从查询行为和点击行为两个角度对网络用户的健康信息检索行为进行研究。查询行为的研究指标包括会话层(会话长度、用户重复查询), 查询串层(查询串长度、重复查询)和词项层(高频词汇, 主题分类);点击行为的研究指标为点击位置和点击内容。[结果/结论] 健康相关查询的重复率较高, 提示相关网站可缓存高重复率查询串的返回结果;大众关注的热点领域为疾病、保健、母婴、医疗机构与美容整形, 提示网站的导航设计注意导航方向;用户更偏爱使用问答型平台, 提示网站设计者应更加关注与用户间问答型的互动模式。 相似文献
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Spink A Yang Y Jansen J Nykanen P Lorence DP Ozmutlu S Ozmutlu HC 《Health information and libraries journal》2004,21(1):44-51
This paper reports findings from an analysis of medical or health queries to different web search engines. We report results: (i). comparing samples of 10000 web queries taken randomly from 1.2 million query logs from the AlltheWeb.com and Excite.com commercial web search engines in 2001 for medical or health queries, (ii). comparing the 2001 findings from Excite and AlltheWeb.com users with results from a previous analysis of medical and health related queries from the Excite Web search engine for 1997 and 1999, and (iii). medical or health advice-seeking queries beginning with the word 'should'. Findings suggest: (i). a small percentage of web queries are medical or health related, (ii). the top five categories of medical or health queries were: general health, weight issues, reproductive health and puberty, pregnancy/obstetrics, and human relationships, and (iii). over time, the medical and health queries may have declined as a proportion of all web queries, as the use of specialized medical/health websites and e-commerce-related queries has increased. Findings provide insights into medical and health-related web querying and suggests some implications for the use of the general web search engines when seeking medical/health information. 相似文献
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Bing and Google customize their results to target people with different geographic locations and languages but, despite the importance of search engines for web users and webometric research, the extent and nature of these differences are unknown. This study compares the results of seventeen random queries submitted automatically to Bing for thirteen different English geographic search markets at monthly intervals. Search market choice alters a small majority of the top 10 results but less than a third of the complete sets of results. Variation in the top 10 results over a month was about the same as variation between search markets but variation over time was greater for the complete results sets. Most worryingly for users, there were almost no ubiquitous authoritative results: only one URL was always returned in the top 10 for all search markets and points in time, and Wikipedia was almost completely absent from the most common top 10 results. Most importantly for webometrics, results from at least three different search markets should be combined to give more reliable and comprehensive results, even for queries that return fewer than the maximum number of URLs. 相似文献
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Search engine results are often biased towards a certain aspect of a query or towards a certain meaning for ambiguous query terms. Diversification of search results offers a way to supply the user with a better balanced result set increasing the probability that a user finds at least one document suiting her information need. In this paper, we present a reranking approach based on minimizing variance of Web search results to improve topic coverage in the top-k results. We investigate two different document representations as the basis for reranking. Smoothed language models and topic models derived by Latent Dirichlet?allocation. To evaluate our approach we selected 240 queries from Wikipedia disambiguation pages. This provides us with ambiguous queries together with a community generated balanced representation of their (sub)topics. For these queries we crawled two major commercial search engines. In addition, we present a new evaluation strategy based on Kullback-Leibler divergence and Wikipedia. We evaluate this method using the TREC sub-topic evaluation on the one hand, and manually annotated query results on the other hand. Our results show that minimizing variance in search results by reranking relevant pages significantly improves topic coverage in the top-k results with respect to Wikipedia, and gives a good overview of the overall search result. Moreover, latent topic models achieve competitive diversification with significantly less reranking. Finally, our evaluation reveals that our automatic evaluation strategy using Kullback-Leibler divergence correlates well with α-nDCG scores used in manual evaluation efforts. 相似文献
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Query suggestion, which enables the user to revise a query with a single click, has become one of the most fundamental features of Web search engines. However, it has not been clear what circumstances cause the user to turn to query suggestion. In order to investigate when and how the user uses query suggestion, we analyzed three kinds of data sets obtained from a major commercial Web search engine, comprising approximately 126 million unique queries, 876 million query suggestions and 306 million action patterns of users. Our analysis shows that query suggestions are often used (1) when the original query is a rare query, (2) when the original query is a single-term query, (3) when query suggestions are unambiguous, (4) when query suggestions are generalizations or error corrections of the original query, and (5) after the user has clicked on several URLs in the first search result page. Our results suggest that search engines should provide better assistance especially when rare or single-term queries are input, and that they should dynamically provide query suggestions according to the searcher’s current state. 相似文献
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Measuring Search Engine Quality 总被引：12，自引：3，他引：9
The effectiveness of twenty public search engines is evaluated using TREC-inspired methods and a set of 54 queries taken from real Web search logs. The World Wide Web is taken as the test collection and a combination of crawler and text retrieval system is evaluated. The engines are compared on a range of measures derivable from binary relevance judgments of the first seven live results returned. Statistical testing reveals a significant difference between engines and high intercorrelations between measures. Surprisingly, given the dynamic nature of the Web and the time elapsed, there is also a high correlation between results of this study and a previous study by Gordon and Pathak. For nearly all engines, there is a gradual decline in precision at increasing cutoff after some initial fluctuation. Performance of the engines as a group is found to be inferior to the group of participants in the TREC-8 Large Web task, although the best engines approach the median of those systems. Shortcomings of current Web search evaluation methodology are identified and recommendations are made for future improvements. In particular, the present study and its predecessors deal with queries which are assumed to derive from a need to find a selection of documents relevant to a topic. By contrast, real Web search reflects a range of other information need types which require different judging and different measures. 相似文献
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The collective feedback of the users of an Information Retrieval (IR) system has been shown to provide semantic information
that, while hard to extract using standard IR techniques, can be useful in Web mining tasks. In the last few years, several
approaches have been proposed to process the logs stored by Internet Service Providers (ISP), Intranet proxies or Web search
engines. However, the solutions proposed in the literature only partially represent the information available in the Web logs.
In this paper, we propose to use a richer data structure, which is able to preserve most of the information available in the
Web logs. This data structure consists of three groups of entities: users, documents and queries, which are connected in a
network of relations. Query refinements correspond to separate transitions between the corresponding query nodes in the graph,
while users are linked to the queries they have issued and to the documents they have selected. The classical query/document
transitions, which connect a query to the documents selected by the users’ in the returned result page, are also considered.
The resulting data structure is a complete representation of the collective search activity performed by the users of a search
engine or of an Intranet. The experimental results show that this more powerful representation can be successfully used in
several Web mining tasks like discovering semantically relevant query suggestions and Web page categorization by topic. 相似文献
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Thanh Tin Tang Nick Craswell David Hawking Kathy Griffiths Helen Christensen 《Information Retrieval》2006,9(2):207-225
When searching for health information, results quality can be judged against available scientific evidence: Do search engines return advice consistent with evidence based medicine? We compared the performance of domain-specific health and depression search engines against a general-purpose engine (Google) on both relevance of results and quality of advice. Over 101 queries, to which the term ‘depression’ was added if not already present, Google returned more relevant results than those of the domain-specific engines. However, over the 50 treatment-related queries, Google returned 70 pages recommending for or against a well studied treatment, of which 19 strongly disagreed with the scientific evidence. A domain-specific index of 4 sites selected by domain experts was only wrong in 5 of 50 recommendations. Analysis suggests a tension between relevance and quality. Indexing more pages can give a greater number of relevant results, but selective inclusion can give better quality. 相似文献
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搜索引擎用户点击行为分析 总被引：9，自引：3，他引：9
基于大规模分布式搜索引擎系统———北大“天网”的用户点击记录,本文研究发现:用户点击不同URL的数量遵从Heaps定律,点击URL的频度频级服从类Zipf分布,点击URL与页面大小相关,点击URL具有时间局部性,其顺序具有自相似性特征等一些具有普适性的规律。提出了利用点击日志确定相近查询词的一个新的有效算法。这些研究结果对于掌握用户的搜索行为,完善搜索引擎系统的设计,提高检索服务的效率和质量具有重要的意义。 相似文献
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国外语义搜索引擎调查与分析 总被引：1，自引：0，他引：1
收集Hakia、SenseBot、Swoogle、Kngine等13种国外典型的语义搜索引擎,以用户体验为视角,通过网站访问与实例测试,对其功能定位、检索范围和检索方法,尤其是语义搜索技术、结果呈现方式等进行深入调查与分析。研究表明,与传统搜索引擎链接清单相比,语义搜索引擎可为查询提供更加精准与直接的答案,能为用户提供更智能化、人性化、知识化的服务。最后对语义搜索引擎存在的问题、局限性和发展趋势进行讨论与展望。 相似文献
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中文搜索引擎用户检索式特征探析 总被引：2，自引：0，他引：2
这项研究采集了百度、一搜、中搜和搜狗四家中文搜索引擎的七千余项检索式,分别从词汇出现频次、词汇量、类别等方面分析了中文搜索引擎用户的检索行为特征,对开展用户教育和搜索服务设计都有一定的实用价值。 相似文献
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中文搜索引擎的搜索结果重合率研究 总被引：1，自引：0，他引：1
本文的研究目的是测试主流中文搜索引擎搜索结果之间的重合程度和差异程度.利用一个具有11 171条来自真实用户的提问样本集对百度、谷歌和中国雅虎进行实际测试,发现中文搜索引擎搜索结果之间的差异很大,重合率很低.在全部的第一页搜索结果中,三个引擎中任何一个引擎独有的搜索结果总数占89.34%,任何两个引擎之间重合的搜索结果总数占8.11%,三个引擎重合的搜索结果数量占2.54%.三个引擎前两页搜索结果的重合比例更低.通过和已有的英文搜索引擎重合率测试数据相比较,发现中英文搜索引擎的搜索结果重合率都很低,且很相近. 相似文献
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Ruihua Song Dingquan Wang Jian-Yun Nie Ji-Rong Wen Yong Yu 《Information Retrieval》2016,19(6):573-593
Users often issue all kinds of queries to look for the same target due to the intrinsic ambiguity and flexibility of natural languages. Some previous work clusters queries based on co-clicks; however, the intents of queries in one cluster are not that similar but roughly related. It is desirable to conduct automatic mining of queries with equivalent intents from a large scale search logs. In this paper, we take account of similarities between query strings. There are two issues associated with such similarities: it is too costly to compare any pair of queries in large scale search logs, and two queries with a similar formulation, such as “SVN” (Apache Subversion) and support vector machine (SVM), are not necessarily similar in their intents. To address these issues, we propose using the similarities of query strings above the co-click based clustering results. Our method improves precision over the co-click based clustering method (lifting precision from 0.37 to 0.62), and outperforms a commercial search engine’s query alteration (lifting \(F_1\) measure from 0.42 to 0.56). As an application, we consider web document retrieval. We aggregate similar queries’ click-throughs with the query’s click-throughs and evaluate them on a large scale dataset. Experimental results indicate that our proposed method significantly outperforms the baseline method of using a query’s own click-throughs in all metrics. 相似文献
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Large sets of Web page links, colinks, or URLs sometimes need to be counted or otherwise summarized by researchers to analyze Web growth or publishing. Computing professionals also use them to evaluate Web sites or optimize search engines. Despite the apparently simple nature of these types of data, many different summarization methods have been used in the past. Some of these methods may not have been optimal. This article proposes a generic lexical framework to unify and extend existing methods through abstract notions of link lists and URL lists. The approach is built upon decomposing URLs by lexical segments, such as domain names, and systematically characterizing the counting options available. In addition, counting method choice recommendations are inferred from a very general set of theoretical research assumptions. The article also offers practical advice for analyzing raw data from search engines. 相似文献
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Query structuring and expansion with two-stage term dependence for Japanese web retrieval 总被引：1，自引：1，他引：0
In this paper, we propose a new term dependence model for information retrieval, which is based on a theoretical framework
using Markov random fields. We assume two types of dependencies of terms given in a query: (i) long-range dependencies that
may appear for instance within a passage or a sentence in a target document, and (ii) short-range dependencies that may appear
for instance within a compound word in a target document. Based on this assumption, our two-stage term dependence model captures
both long-range and short-range term dependencies differently, when more than one compound word appear in a query. We also
investigate how query structuring with term dependence can improve the performance of query expansion using a relevance model.
The relevance model is constructed using the retrieval results of the structured query with term dependence to expand the
query. We show that our term dependence model works well, particularly when using query structuring with compound words, through
experiments using a 100-gigabyte test collection of web documents mostly written in Japanese. We also show that the performance
of the relevance model can be significantly improved by using the structured query with our term dependence model.
相似文献
| Koji EguchiEmail: |
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从Sogou查询日志中选取样本查询且进行人工标注,通过对标注后新闻查询的分析,提出能用于识别新闻意图的新特征,即查询表达式特征、查询随时间分布特征以及点击结果特征。根据这3个特征,利用决策树分类器实现查询中新闻意图的自动识别,结果发现:①新闻类查询的查询目标主要集中在特定主题信息以及娱乐类信息方面,其查询主题大多为娱乐、政治、体育与经济类信息;②相对非新闻查询,新闻查询具有更可能包含实体、随时间分布波动较大、点击结果之间相似度更高的特点;③本方法对查询中新闻意图的识别效果较好,其宏平均准确率、召回率、F值分别为 0.76、0.73、0、74。 相似文献
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Qinglei Wang Yanan Qian Ruihua Song Zhicheng Dou Fan Zhang Tetsuya Sakai Qinghua Zheng 《Information Retrieval》2013,16(4):484-503
Web search queries are often ambiguous or faceted, and the task of identifying the major underlying senses and facets of queries has received much attention in recent years. We refer to this task as query subtopic mining. In this paper, we propose to use surrounding text of query terms in top retrieved documents to mine subtopics and rank them. We first extract text fragments containing query terms from different parts of documents. Then we group similar text fragments into clusters and generate a readable subtopic for each cluster. Based on the cluster and the language model trained from a query log, we calculate three features and combine them into a relevance score for each subtopic. Subtopics are finally ranked by balancing relevance and novelty. Our evaluation experiments with the NTCIR-9 INTENT Chinese Subtopic Mining test collection show that our method significantly outperforms a query log based method proposed by Radlinski et al. (2010) and a search result clustering based method proposed by Zeng et al. (2004) in terms of precision, I-rec, D-nDCG and D#-nDCG, the official evaluation metrics used at the NTCIR-9 INTENT task. Moreover, our generated subtopics are significantly more readable than those generated by the search result clustering method. 相似文献