中文搜索引擎用户检索式特征探析

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。     

中文搜索引擎的搜索结果重合率研究

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.     

基于公共与非公共检索计算机的OPAC检索行为比较研究

[目的/意义] 探讨用户在公共检索和非公共检索计算机上进行OPAC检索的行为共性与差异。[方法/过程] 以北京师范大学图书馆OPAC日志数据为例,对图书馆内公共检索计算机和馆外典型非公共检索计算机产生的日志信息进行分析,从基本特征、一次检索会话内的检索行为特征两方面,对两类计算机用户的OPAC检索行为进行比较。[结果/结论] 公共检索计算机用户与非公共检索计算机用户在关键检索行为的表现上具有高度的一致性,包括检索点与高级检索功能的使用、一次检索会话内的提问调整方式等。同时,两类用户在一次检索会话的提问次数、持续时间、两次检索会话时间间隔等方面表现出差异。     

Will Web Search Engines Replace Bibliographic Databases in the Systematic Identification of Research?

The availability of web search engines offers opportunities in addition to those provided by bibliographic databases for identifying academic literature, but their usefulness for retrieving research is uncertain. A rigorous literature search was undertaken to investigate whether web search engines might replace bibliographic databases, using empirical research in health and social care as a case study. Eight databases and five web search engines were searched between 20 July and 6 August 2015. Sixteen unique studies which compared at least one database with at least one web search engine were examined, as well as drawing lessons from the authors’ own search process. Web search engines were limited in that the searcher cannot be certain that the principles of Boolean logic apply and they were more limited than bibliographic databases in their functions, such as exporting abstracts. Recommendations are made for improving the rigour and quality of reporting studies of academic literature searching.     

几种搜索引擎中Image搜索的比较

随着用户对网上图像搜索要求的不断增长，各种基于Web的图像搜索引擎应运而生。但是各种不同的图像搜索引擎在搜索的响应时间、检索出的图像的数量、准确性、检索结果的排序等方面存在着较大的差异。本文首先就图像搜索模式作一简单的叙述，然后对搜索引擎Google、Excite、Yahoo、Ixqiuck的Image Search进行比较。     

Identifying top relevant dates for implicit time sensitive queries

Despite a clear improvement of search and retrieval temporal applications, current search engines are still mostly unaware of the temporal dimension. Indeed, in most cases, systems are limited to offering the user the chance to restrict the search to a particular time period or to simply rely on an explicitly specified time span. If the user is not explicit in his/her search intents (e.g., “philip seymour hoffman”) search engines may likely fail to present an overall historic perspective of the topic. In most such cases, they are limited to retrieving the most recent results. One possible solution to this shortcoming is to understand the different time periods of the query. In this context, most state-of-the-art methodologies consider any occurrence of temporal expressions in web documents and other web data as equally relevant to an implicit time sensitive query. To approach this problem in a more adequate manner, we propose in this paper the detection of relevant temporal expressions to the query. Unlike previous metadata and query log-based approaches, we show how to achieve this goal based on information extracted from document content. However, instead of simply focusing on the detection of the most obvious date we are also interested in retrieving the set of dates that are relevant to the query. Towards this goal, we define a general similarity measure that makes use of co-occurrences of words and years based on corpus statistics and a classification methodology that is able to identify the set of top relevant dates for a given implicit time sensitive query, while filtering out the non-relevant ones. Through extensive experimental evaluation, we mean to demonstrate that our approach offers promising results in the field of temporal information retrieval (T-IR), as demonstrated by the experiments conducted over several baselines on web corpora collections.     

A study of medical and health queries to web search engines

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.     

基于用户日志的移动搜索行为分析

认为移动搜索用户行为特征与规律的发现,对移动搜索服务的改进具有重要的参考价值。基于国内某大型学术类网站一批包含300余万条有效记录的日志数据,分析查询串、搜索时间的分布、搜索会话、移动搜索设备终端等我国移动搜索用户行为的基本特征指标。研究结果显示:与传统PC搜索相比,移动用户的查询时间分布更均匀,会话更短,使用查询推荐比例更少,移动智能终端设备用户搜索更频繁。     

Search engines’ responses to several search feature selections

The authors of this paper investigated the impact of the advanced search features of three common search engines on retrieval result performance: Yahoo, Google, and Live Search. The authors analyzed 240 search queries with different information need emphases to determine retrieval effectiveness differences among regular search, title search, exact phrase search, and PDF file format restriction search. A one-way ANOVA method and regression analysis method were used for the study. It was found that the PDF file format restriction search achieved the best retrieval performance among Yahoo, Google and Live Search. The regular search achieved the best web page ranking performance among Yahoo, Google, and Live Search. The findings of this study can be used to assist users in formulating an appropriate search strategy to improve search effectiveness, and to shed light on how search engines react to different types of search features in terms of retrieval effectiveness.     

Search engines’ responses to several search feature selections

The authors of this paper investigated the impact of the advanced search features of three common search engines on retrieval result performance: Yahoo, Google, and Live Search. The authors analyzed 240 search queries with different information need emphases to determine retrieval effectiveness differences among regular search, title search, exact phrase search, and PDF file format restriction search. A one-way ANOVA method and regression analysis method were used for the study. It was found that the PDF file format restriction search achieved the best retrieval performance among Yahoo, Google and Live Search. The regular search achieved the best web page ranking performance among Yahoo, Google, and Live Search. The findings of this study can be used to assist users in formulating an appropriate search strategy to improve search effectiveness, and to shed light on how search engines react to different types of search features in terms of retrieval effectiveness.     

Accounting for the knowledge gained during a web search: An empirical study on learning transfer indicators

Searches with learning intent typically require the users to interact with the searching environment and perform knowledge acquisition features such as scan, read, and process the online content to fulfill their information needs. To capture indicators from searching behaviors that could account for the knowledge gained during a Web search, a qualitative study was performed using the Concurrent Think-Aloud protocol to observe the mechanisms of transfer and map knowledge flows during 78 search sessions. Findings indicate evidence of transfer of learning in the form of sixteen online information searching strategy indicators. This research aids the understanding of how knowledge is gained during search sessions and how to identify behaviors that could indicate that learning has occurred, which could be used to represent knowledge gain on Web search engines. In this way, it can aid search engines to become not only better tools of searching, but also tools of learning.     

A Student Perspective on e-Resource Discovery: Has the Google Factor Changed Publisher Platform Searching Forever?

The literature shows that students are more likely to begin their search via Google, as it is perceived to be easier and more accessible than other databases or publisher platforms. The invisible web, specifically publisher platforms, is sometimes too difficult for students to access; there are also suggestions that Google Scholar in particular may outperform other paid-for databases. The ease of access and the somewhat misguided notion that Google Scholar has more reliable information than that provided by libraries makes search engines all the more attractive. This culture of searching using a single search box is reflected in the increase in the number of libraries opting for single resource discovery systems such as Summon or Primo, which use a single search covering all the library holdings. The findings suggest that whilst Google Scholar can perform well in some circumstances, it performed only moderately well when compared with LISTA and Summon – the single resource discovery system tested. It was the least successful resource in terms of precision when compared with LISTA, Summon, Emerald and Sage. However, the simplicity of search engines begs the question: will databases and publisher platforms become obsolete? The study concludes that subject specific databases are more effective than search engines, but the complexity of accessing the invisible web is hindering their popularity.     

网络影响因子实证研究:基于不同搜索引擎的大学网站影响力分析

利用AltaVista、Fast、Google 3种搜索引擎在不同时间对中国大陆10所大学的总网络影响因子进行对比分析,其结果表明:网络影响因子的有效性和可靠性除受其本身定义的局限外,还受到搜索引擎性能的影响;目前根据网络影响因子来分析各大学网站的影响力,并以此来对各大学的综合实力进行排名的做法尚缺乏足够的科学依据。     

基于日志挖掘的用户健康信息检索行为研究

[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。     

基于日志挖掘的学术搜索困难度量方法研究

[目的/意义] 用户检索中经常面临不同程度的信息搜寻困难,为更好地理解用户需求、改进检索系统,需要一种简洁有效的方法度量信息搜寻的困难程度。[方法/过程] 将用户为查询而付出的行为及时间代价作为其信息搜寻困难的体现。按照用户在会话中的行为模式划分会话类型,将查询需求被满足且代价最小的会话类型作为比较基准,用基准会话的代价衡量其他会话类型的困难程度。为优化代价的表达模型,对搜寻代价的行为指标进行相关性检验,用因子分析选择独立性、区分度好的行为特征进行建模。以国家科技图书文献中心（NSTL）日志和搜狗日志为数据集比较学术搜索与通用搜索环境,以及不同会话类型所代表的探索过程中,用户的信息搜寻困难度。[结果/结论] 在本文所度量的两种搜索系统中,用户面临的信息搜寻困难度分别为2.30和1.57,学术搜索中的困难高于通用搜索。在两种体现学术探索过程的会话中,困难度分别为2.35和4.13。本文提出的方法可以用简单的数值来概括具有多种影响因素的搜索困难,并能用于不同类型会话和搜索环境,丰富了检索系统的评估手段。     

网络商业信息资源获取技术探讨

基于网络商业信息资源的分类、特点,从网络数据库、通用搜索引擎、商业搜索引擎、电子图书和商业网站等方面系统地探讨了网络商业信息资源荻取技术.参考文献7.     

1997年－2005年搜索引擎质量评价研究论文定量分析

〔摘要〕 以《中文科技期刊数据库》和《中国期刊网》为数据源,运用文献计量学方法,从论文的发表时间分布、期刊分布、作者分析、主题内容分析和科研立项情况等文献特征对1997年－2005年间收录的搜索引擎质量评价研究论文进行定量分析,以期为本领域今后的研究提供参考与启示。     

Search markets and search results: The case of Bing

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.     

Spelling correction in the PubMed search engine

It is known that users of internet search engines often enter queries with misspellings in one or more search terms. Several web search engines make suggestions for correcting misspelled words, but the methods used are proprietary and unpublished to our knowledge. Here we describe the methodology we have developed to perform spelling correction for the PubMed search engine. Our approach is based on the noisy channel model for spelling correction and makes use of statistics harvested from user logs to estimate the probabilities of different types of edits that lead to misspellings. The unique problems encountered in correcting search engine queries are discussed and our solutions are outlined.     

The development of users' mental models of MedlinePlus in information searching

This study investigated the dynamic process of people constructing mental models of MedlinePlus, a medical information web space, during their interaction with the system. Thirty-eight participants participated in the study. Their mental models of MedlinePlus were measured by a concept listing protocol and an interview method at three time points: after they freely explored the system for 5 min (T1), after the first search session (T2), and after the second search session (T3). The analysis revealed that participants constructed their mental models of MedlinePlus based on the schemas that they have of information-rich web spaces. The model construction process involved changes and development in three parallel dimensions: cognition, emotion, and behavior. The development is enabled and coordinated by three mental activities: assimilating new concepts, modifying existing concepts, and phasing out previously perceived concepts. Furthermore, mental model construction is not only a function of users' internal cognition, but also affected by external cognitive structures, including the system, system feedback, and tasks. Mental model construction is also a process distributed over time. The results suggested that mental models could serve as a framework for guiding user research and system design. The dynamic nature of the mental models indicated that an iterative approach needs to be adopted.