Facing and bridging gaps in Web searching

Drawing on the ideas of the Sense-Making approach, the ways in which people face and bridge gaps in Web searching are analyzed. The empirical study is based on videotaped Web searches conducted by seven participants. Altogether 11 gaps and 13 search tactics of various types were identified. The gaps faced by the searchers originated from three major factors: problematic content of information, insufficient search competence and problems caused by the search environment. Of individual gaps, no relevant material available, inaccessible content and confusion were most frequent. Of the search tactics used in gap-bridging, following links and activating the Back button were most popular. Gaps related to the problematic content of information led the informants to redirect the search to find Web pages that focus better on the search topic. If the movement was stopped by insufficient search competence, the searchers tended to return to material that was familiar from earlier use contexts in order to regain control of the search process. Alternatively, they tried to specify the search terms. In cases where the search was interrupted by technical problems or other factors originating from the search system, gap-bridging aimed at returning to familiar and technically reliable links. The Sense-Making theory provides relevant conceptual tools to approach the dynamic and discontinuous nature of Web searching in terms of gap-facing and gap-bridging. The concept of gap-facing enables a context-sensitive analysis of the ways in which Web search processes may be stopped. Gap-bridging indicates a general level motive to find alternative ways to continue searching.     

How doctors search: A study of query behaviour and the impact on search results

Professional, workplace searching is different from general searching, because it is typically limited to specific facets and targeted to a single answer. We have developed the semantic component (SC) model, which is a search feature that allows searchers to structure and specify the search to context-specific aspects of the main topic of the documents. We have tested the model in an interactive searching study with family doctors with the purpose to explore doctors’ querying behaviour, how they applied the means for specifying a search, and how these features contributed to the search outcome. In general, the doctors were capable of exploiting system features and search tactics during the searching. Most searchers produced well-structured queries that contained appropriate search facets. When searches failed it was not due to query structure or query length. Failures were mostly caused by the well-known vocabulary problem. The problem was exacerbated by using certain filters as Boolean filters. The best working queries were structured into 2–3 main facets out of 3–5 possible search facets, and expressed with terms reflecting the focal view of the search task. The findings at the same time support and extend previous results about query structure and exhaustivity showing the importance of selecting central search facets and express them from the perspective of search task. The SC model was applied in the highest performing queries except one. The findings suggest that the model might be a helpful feature to structure queries into central, appropriate facets, and in returning highly relevant documents.     

Children's query types and reformulations in Google search

We investigated the searching behaviors of twenty-four children in grades 6, 7, and 8 (ages 11–13) in finding information on three types of search tasks in Google. Children conducted 72 search sessions and issued 150 queries. Children's phrase- and question-like queries combined were much more prevalent than keyword queries (70% vs. 30%, respectively). Fifty two percent of the queries were reformulations (33 sessions). We classified children's query reformulation types into five classes based on the taxonomy by Liu et al. (2010). We found that most query reformulations were by Substitution and Specialization, and that children hardly repeated queries. We categorized children's queries by task facets and examined the way they expressed these facets in their query formulations and reformulations. Oldest children tended to target the general topic of search tasks in their queries most frequently, whereas younger children expressed one of the two facets more often. We assessed children's achieved task outcomes using the search task outcomes measure we developed. Children were mostly more successful on the fact-finding and fully self-generated task and partially successful on the research-oriented task. Query type, reformulation type, achieved task outcomes, and expressing task facets varied by task type and grade level. There was no significant effect of query length in words or of the number of queries issued on search task outcomes. The study findings have implications for human intervention, digital literacy, search task literacy, as well as for system intervention to support children's query formulation and reformulation during interaction with Google.     

The effect of user characteristics on search effectiveness in information retrieval

This paper investigates the influence of user characteristics (e.g. search experience and cognitive skills) on user effectiveness. A user study was conducted to investigate this effect, 56 participants completed searches for 56 topics using the TREC test collection. Results indicated that participants with search experience and high cognitive skills were more effective than those with less experience and slower perceptual abilities. However, all users rated themselves with the same level of satisfaction with the search results despite the fact they varied substantially in their effectiveness. Therefore, information retrieval evaluators should take these factors into consideration when investigating the impact of system effectiveness on user effectiveness.     

利用Google进行专题信息检索

Google是当今一个具有强大功能和独到特点的优秀搜索引擎，本文研究Google基本检索和高级检索语法规则;探讨利用Google的语法规则增强Google的关键词检索功能、提高查准率，正确构建检索式，实施专题信息检索的策略。     

Expanding end-users' query statements for free text searching with a search-aid thesaurus

Authors and searchers usually express the same things in many different ways, which causes problems in free text searching of text databases. Thus, a switching tool connecting the different names of one concept is needed. This study tests the effectiveness of a thesaurus as a search-aid in free text searching of a full text database. A set of queries was searched against a large full text database of newspaper articles. The search-aid thesaurus constructed for the test contains the usual relationships of a thesaurus, namely equivalence, hierarchical, and associative relationships. Each query was searched in five distinct modes: basic search, synonym search, narrower term search, related term search, and union of all previous searches. The basic searches contained only terms included in the original query statements. In the synonym searches, the terms of the basic search were extended by disjunction of the synonyms given by the search-aid thesaurus without modifying the overall logic of the basic search. Likewise, the basic search was extended in turn with the narrower terms and with the related terms given by the search-aid thesaurus. The last search mode included the basic terms and all the terms used in the previous searches. The searches were analyzed in terms of relative recall and precision; relative recall was estimated by setting the recall of the union search to 100%. On the average the value of relative recall was 47.2% in the basic search, compared with 100% in the union search; the average value of precision decreased only from 62.5% in the basic search to 51.2% in the union search.     

Users can change their web search tactics: Design guidelines for categorized overviews

Categorized overviews of web search results are a promising way to support user exploration, understanding, and discovery. These search interfaces combine a metadata-based overview with the list of search results to enable a rich form of interaction. A study of 24 sophisticated users carrying out complex tasks suggests how searchers may adapt their search tactics when using categorized overviews. This mixed methods study evaluated categorized overviews of web search results organized into thematic, geographic, and government categories. Participants conducted four exploratory searches during a 2-hour session to generate ideas for newspaper articles about specified topics such as “human smuggling.” Results showed that subjects explored deeper while feeling more organized, and that the categorized overview helped subjects better assess their results, although no significant differences were detected in the quality of the article ideas. A qualitative analysis of searcher comments identified seven tactics that participants reported adopting when using categorized overviews. This paper concludes by proposing a set of guidelines for the design of exploratory search interfaces. An understanding of the impact of categorized overviews on search tactics will be useful to web search researchers, search interface designers, information architects and web developers.     

Amount of invested mental effort (AIME) in online searching

This research investigates how people’s perceptions of information retrieval (IR) systems, their perceptions of search tasks, and their perceptions of self-efficacy influence the amount of invested mental effort (AIME) they put into using two different IR systems: a Web search engine and a library system. It also explores the impact of mental effort on an end user’s search experience. To assess AIME in online searching, two experiments were conducted using these methods: Experiment 1 relied on self-reports and Experiment 2 employed the dual-task technique. In both experiments, data were collected through search transaction logs, a pre-search background questionnaire, a post-search questionnaire and an interview. Important findings are these: (1) subjects invested greater mental effort searching a library system than searching the Web; (2) subjects put little effort into Web searching because of their high sense of self-efficacy in their searching ability and their perception of the easiness of the Web; (3) subjects did not recognize that putting mental effort into searching was something needed to improve the search results; and (4) data collected from multiple sources proved to be effective for assessing mental effort in online searching.     

Automatic suggestion of phrasal-concept queries for literature search

Both general and domain-specific search engines have adopted query suggestion techniques to help users formulate effective queries. In the specific domain of literature search (e.g., finding academic papers), the initial queries are usually based on a draft paper or abstract, rather than short lists of keywords. In this paper, we investigate phrasal-concept query suggestions for literature search. These suggestions explicitly specify important phrasal concepts related to an initial detailed query. The merits of phrasal-concept query suggestions for this domain are their readability and retrieval effectiveness: (1) phrasal concepts are natural for academic authors because of their frequent use of terminology and subject-specific phrases and (2) academic papers describe their key ideas via these subject-specific phrases, and thus phrasal concepts can be used effectively to find those papers. We propose a novel phrasal-concept query suggestion technique that generates queries by identifying key phrasal-concepts from pseudo-labeled documents and combines them with related phrases. Our proposed technique is evaluated in terms of both user preference and retrieval effectiveness. We conduct user experiments to verify a preference for our approach, in comparison to baseline query suggestion methods, and demonstrate the effectiveness of the technique with retrieval experiments.     

Generating suggestions for queries in the long tail with an inverted index

This paper proposes an efficient and effective solution to the problem of choosing the queries to suggest to web search engine users in order to help them in rapidly satisfying their information needs. By exploiting a weak function for assessing the similarity between the current query and the knowledge base built from historical users’ sessions, we re-conduct the suggestion generation phase to the processing of a full-text query over an inverted index. The resulting query recommendation technique is very efficient and scalable, and is less affected by the data-sparsity problem than most state-of-the-art proposals. Thus, it is particularly effective in generating suggestions for rare queries occurring in the long tail of the query popularity distribution. The quality of suggestions generated is assessed by evaluating the effectiveness in forecasting the users’ behavior recorded in historical query logs, and on the basis of the results of a reproducible user study conducted on publicly-available, human-assessed data. The experimental evaluation conducted shows that our proposal remarkably outperforms two other state-of-the-art solutions, and that it can generate useful suggestions even for rare and never seen queries.     

Multimedia search capabilities of Chinese language search engines

This paper reports results from a study exploring the multimedia search functionality of Chinese language search engines. Web searching in Chinese (Mandarin) is a growing research area and a technical challenge for popular commercial Web search engines. Few studies have been conducted on Chinese language search engines. We investigate two research questions: which Chinese language search engines provide multimedia searching, and what multimedia search functionalities are available in Chinese language Web search engines. Specifically, we examine each Web search engine’s (1) features permitting Chinese language multimedia searches, (2) extent of search personalization and user control of multimedia search variables, and (3) the relationships between Web search engines and their features in the Chinese context. Key findings show that Chinese language Web search engines offer limited multimedia search functionality, and general search engines provide a wider range of features than specialized multimedia search engines. Study results have implications for Chinese Web users, Website designers and Web search engine developers.     

Real time search on the web: Queries,topics, and economic value

Real time search is an increasingly important area of information seeking on the Web. In this research, we analyze 1,005,296 user interactions with a real time search engine over a 190 day period. Using query log analysis, we investigate searching behavior, categorize search topics, and measure the economic value of this real time search stream. We examine aggregate usage of the search engine, including number of users, queries, and terms. We then classify queries into subject categories using the Google Directory topical hierarchy. We next estimate the economic value of the real time search traffic using the Google AdWords keyword advertising platform. Results shows that 30% of the queries were unique (used only once in the entire dataset), which is low compared to traditional Web searching. Also, 60% of the search traffic comes from the search engine’s application program interface, indicating that real time search is heavily leveraged by other applications. There are many repeated queries over time via these application program interfaces, perhaps indicating both long term interest in a topic and the polling nature of real time queries. Concerning search topics, the most used terms dealt with technology, entertainment, and politics, reflecting both the temporal nature of the queries and, perhaps, an early adopter user-based. However, 36% of the queries indicate some geographical affinity, pointing to a location-based aspect to real time search. In terms of economic value, we calculate this real time search stream to be worth approximately US $33,000,000 (US $33 M) on the online advertising market at the time of the study. We discuss the implications for search engines and content providers as real time content increasingly enters the main stream as an information source.     

Search tactics used in solving everyday how-to technical tasks: Repertoire,selection and tenacity

With greater access to computational resources, people use search to address many everyday challenges in their lives, including solving technology problems. Although there are now many useful ‘how-to’ resources online (especially videos on YouTube), it can still be difficult to identify, understand, and resolve certain kinds of technical problem. While research tasks have been studied for many years and we know the tactics people use, we know far less about searchers’ tactics for how-to technical tasks that involve actually being able to apply found information to resolve a problem. Crucial to our study was developing and studying a highly realistic, how-to technical task, for which there was no single guidance resource: making a phone safe for a child. After providing 39 participants with an actual phone to fix, and a search engine to perform the task, we analysed their search tactics using retrospective cued think aloud interviews. Our primary contribution is a set of 77 tactics used, in three categories, along with detail of how common they were. We conclude that people had a lot of tactics in their repertoire. Although it was not hard for participants to find relevant information, what was hard was for participants to find information they could use; indeed only 23% of participants successfully completed the entire task. Domain knowledge affected the choice of tactics used (although not necessarily towards better task success). We discuss these influences and make design recommendations for how future search systems can support those in resolving how-to technical tasks.     

New query suggestion framework and algorithms: A case study for an educational search engine

Query suggestion is generally an integrated part of web search engines. In this study, we first redefine and reduce the query suggestion problem as “comparison of queries”. We then propose a general modular framework for query suggestion algorithm development. We also develop new query suggestion algorithms which are used in our proposed framework, exploiting query, session and user features. As a case study, we use query logs of a real educational search engine that targets K-12 students in Turkey. We also exploit educational features (course, grade) in our query suggestion algorithms. We test our framework and algorithms over a set of queries by an experiment and demonstrate a 66–90% statistically significant increase in relevance of query suggestions compared to a baseline method.     

Evaluating WordBars in exploratory Web search scenarios

Web searchers commonly have difficulties crafting queries to fulfill their information needs; even after they are able to craft a query, they often find it challenging to evaluate the results of their Web searches. Sources of these problems include the lack of support for constructing and refining queries, and the static nature of the list-based representations of Web search results. WordBars has been developed to assist users in their Web search and exploration tasks. This system provides a visual representation of the frequencies of the terms found in the first 100 document surrogates returned from an initial query, in the form of a histogram. Exploration of the search results is supported through term selection in the histogram, resulting in a re-sorting of the search results based on the use of the selected terms in the document surrogates. Terms from the histogram can be easily added or removed from the query, generating a new set of search results. Examples illustrate how WordBars can provide valuable support for query refinement and search results exploration, both when vague and specific initial queries are provided. User evaluations with both expert and intermediate Web searchers illustrate the benefits of the interactive exploration features of WordBars in terms of effectiveness as well as subjective measures. Although differences were found in the demographics of these two user groups, both were able to benefit from the features of WordBars.     

Characteristics of character usage in Chinese Web searching

The use of non-English Web search engines has been prevalent. Given the popularity of Chinese Web searching and the unique characteristics of Chinese language, it is imperative to conduct studies with focuses on the analysis of Chinese Web search queries. In this paper, we report our research on the character usage of Chinese search logs from a Web search engine in Hong Kong. By examining the distribution of search query terms, we found that users tended to use more diversified terms and that the usage of characters in search queries was quite different from the character usage of general online information in Chinese. After studying the Zipf distribution of n-grams with different values of n, we found that the curve of unigram is the most curved one of all while the bigram curve follows the Zipf distribution best, and that the curves of n-grams with larger n (n = 3–6) had similar structures with β-values in the range of 0.66–0.86. The distribution of combined n-grams was also studied. All the analyses are performed on the data both before and after the removal of function terms and incomplete terms and similar findings are revealed. We believe the findings from this study have provided some insights into further research in non-English Web searching and will assist in the design of more effective Chinese Web search engines.     

Automatic new topic identification using multiple linear regression

The purpose of this study is to provide automatic new topic identification of search engine query logs, and estimate the effect of statistical characteristics of search engine queries on new topic identification. By applying multiple linear regression and multi-factor ANOVA on a sample data log from the Excite search engine, we demonstrated that the statistical characteristics of Web search queries, such as time interval, search pattern and position of a query in a user session, are effective on shifting to a new topic. Multiple linear regression is also a successful tool for estimating topic shifts and continuations. The findings of this study provide statistical proof for the relationship between the non-semantic characteristics of Web search queries and the occurrence of topic shifts and continuations.     

Factors affecting the selection of search tactics: Tasks,knowledge, process,and systems

This study investigated whether and how different factors in relation to task, user-perceived knowledge, search process, and system affect users’ search tactic selection. Thirty-one participants, representing the general public with their own tasks, were recruited for this study. Multiple methods were employed to collect data, including pre-questionnaire, verbal protocols, log analysis, diaries, and post-questionnaires. Statistical analysis revealed that seven factors were significantly associated with tactic selection. These factors consist of work task types, search task types, familiarity with topic, search skills, search session length, search phases, and system types. Moreover, the study also discovered, qualitatively, in what ways these factors influence the selection of search tactics. Based on the findings, the authors discuss practical implications for system design to support users’ application of multiple search tactics for each factor.     

Tagging and searching: Search retrieval effectiveness of folksonomies on the World Wide Web

Many Web sites have begun allowing users to submit items to a collection and tag them with keywords. The folksonomies built from these tags are an interesting topic that has seen little empirical research. This study compared the search information retrieval (IR) performance of folksonomies from social bookmarking Web sites against search engines and subject directories. Thirty-four participants created 103 queries for various information needs. Results from each IR system were collected and participants judged relevance. Folksonomy search results overlapped with those from the other systems, and documents found by both search engines and folksonomies were significantly more likely to be judged relevant than those returned by any single IR system type. The search engines in the study had the highest precision and recall, but the folksonomies fared surprisingly well. Del.icio.us was statistically indistinguishable from the directories in many cases. Overall the directories were more precise than the folksonomies but they had similar recall scores. Better query handling may enhance folksonomy IR performance further. The folksonomies studied were promising, and may be able to improve Web search performance.