1,018 research outputs found

    Why People Search for Images using Web Search Engines

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    What are the intents or goals behind human interactions with image search engines? Knowing why people search for images is of major concern to Web image search engines because user satisfaction may vary as intent varies. Previous analyses of image search behavior have mostly been query-based, focusing on what images people search for, rather than intent-based, that is, why people search for images. To date, there is no thorough investigation of how different image search intents affect users' search behavior. In this paper, we address the following questions: (1)Why do people search for images in text-based Web image search systems? (2)How does image search behavior change with user intent? (3)Can we predict user intent effectively from interactions during the early stages of a search session? To this end, we conduct both a lab-based user study and a commercial search log analysis. We show that user intents in image search can be grouped into three classes: Explore/Learn, Entertain, and Locate/Acquire. Our lab-based user study reveals different user behavior patterns under these three intents, such as first click time, query reformulation, dwell time and mouse movement on the result page. Based on user interaction features during the early stages of an image search session, that is, before mouse scroll, we develop an intent classifier that is able to achieve promising results for classifying intents into our three intent classes. Given that all features can be obtained online and unobtrusively, the predicted intents can provide guidance for choosing ranking methods immediately after scrolling

    Learning to Attend, Copy, and Generate for Session-Based Query Suggestion

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    Users try to articulate their complex information needs during search sessions by reformulating their queries. To make this process more effective, search engines provide related queries to help users in specifying the information need in their search process. In this paper, we propose a customized sequence-to-sequence model for session-based query suggestion. In our model, we employ a query-aware attention mechanism to capture the structure of the session context. is enables us to control the scope of the session from which we infer the suggested next query, which helps not only handle the noisy data but also automatically detect session boundaries. Furthermore, we observe that, based on the user query reformulation behavior, within a single session a large portion of query terms is retained from the previously submitted queries and consists of mostly infrequent or unseen terms that are usually not included in the vocabulary. We therefore empower the decoder of our model to access the source words from the session context during decoding by incorporating a copy mechanism. Moreover, we propose evaluation metrics to assess the quality of the generative models for query suggestion. We conduct an extensive set of experiments and analysis. e results suggest that our model outperforms the baselines both in terms of the generating queries and scoring candidate queries for the task of query suggestion.Comment: Accepted to be published at The 26th ACM International Conference on Information and Knowledge Management (CIKM2017

    Why people search for images using web search engines

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    What are the intents or goals behind human interactions with image search engines? Knowing why people search for images is of major concern to Web image search engines because user satisfaction may vary as intent varies. Previous analyses of image search behavior have mostly been query-based, focusing on what images people search for, rather than intent-based, that is, why people search for images. To date, there is no thorough investigation of how different image search intents affect users' search behavior. In this paper, we address the following questions: (1) Why do people search for images in text-based Web image search systems? (2) How does image search behavior

    DYNIQX: A novel meta-search engine for the web

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    The effect of metadata in collection fusion has not been sufficiently studied. In response to this, we present a novel meta-search engine called Dyniqx for metadata based search. Dyniqx integrates search results from search services of documents, images, and videos for generating a unified list of ranked search results. Dyniqx exploits the availability of metadata in search services such as PubMed, Google Scholar, Google Image Search, and Google Video Search etc for fusing search results from heterogeneous search engines. In addition, metadata from these search engines are used for generating dynamic query controls such as sliders and tick boxes etc which are used by users to filter search results. Our preliminary user evaluation shows that Dyniqx can help users complete information search tasks more efficiently and successfully than three well known search engines respectively. We also carried out one controlled user evaluation of the integration of six document/image/video based search engines (Google Scholar, PubMed, Intute, Google Image, Yahoo Image, and Google Video) in Dyniqx. We designed a questionnaire for evaluating different aspect of Dyniqx in assisting users complete search tasks. Each user used Dyniqx to perform a number of search tasks before completing the questionnaire. Our evaluation results confirm the effectiveness of the meta-search of Dyniqx in assisting user search tasks, and provide insights into better designs of the Dyniqx' interface

    SEARCHING AS THINKING: THE ROLE OF CUES IN QUERY REFORMULATION

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    Given the growing volume of information that surrounds us, search, and particularly web search, is now a fundamental part of how people perceive and experience the world. Understanding how searchers interact with search engines is thus an important topic both for designers of information retrieval systems and educators working in the area of digital literacy. Reaching such understanding, however, with the more established, system-centric, approaches in information retrieval (IR) is limited. While inherently iterative nature of the search process is generally acknowledged in the field of IR, research on query reformulation is typically limited to dealing with the what or the how of the query reformulation process. Drawing a complete picture of searchers\u27 behavior is thus incomplete without addressing the why of query reformulation, including what pieces of information, or cues, trigger the reformulation process. Unpacking that aspect of the searchers\u27 behavior requires a more user-centric approach. The overall goal of this study is to advance understanding of the reformulation process and the cues that influence it. It was driven by two broad questions about the use of cues (on the search engine result pages or the full web pages) in the searchers\u27 decisions regarding query reformulation and the effects of that use on search effectiveness. The study draws on data collected in a lab setting from a sample of students who performed a series of search tasks and then went through a process of stimulated recall focused on their query reformulations. Both, query reformulations recorded during the search tasks and cues elicited during the stimulated recall exercise, were coded and then modeled using the mixed effects method. The final models capture the relationships between cues and query reformulation strategies as well as cues and search effectiveness; in both cases some relationships are moderated by search expertise and domain knowledge. The results demonstrate that searchers systematically elicit and use cues with regard to query reformulation. Some of these relationships are independent from search expertise and domain knowledge, while others manifest themselves differently at different levels of search expertise and domain knowledge. Similarly, due to the fact that the majority of the reformulations in this study indicated a failure of the preceding query, mixed results were achieved with identifying relationships between the use of cues and search effectiveness. As a whole, this work offers two contributions to the field of user-centered information retrieval. First, it reaffirms some of the earlier conceptual work about the role of cues in search behavior, and then expands on it by proposing specific relationships between cues and reformulations. Second, it highlights potential design considerations in creating search engine results pages and query term suggestions, as well as and training suggestion for educators working on digital literacy

    Analysis of web information-seeking behavior of users with different levels of health literacy

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    Literacia em Saúde é definida como "o nível pelo qual os indivíduos podem obter, processar, compreender e comunicar informação relacionada com saúde necessária para tomar decisões de saúde informadas". Os utilizadores com um baixo nível de literacia em saúde têm menos conhecimentos das suas condições médicas, maior dificuldade em seguir as instruções e compreender a informação dada pelos médicos. Cada vez mais, as pessoas recorrem à web para pesquisar sobre informação de saúde. As dificuldades que os utilizadores de baixa literacia têm no mundo real provavelmente persistem no mundo virtual. O principal objetivo deste estudo é analisar os comportamentos de pesquisa de utilizadores com diferentes níveis de literacia em saúde. Pretende-se identificar diferenças entre pessoas com baixa e alta literacia de saúde que depois possam ser utilizadas para a melhoria dos sistemas de recuperação e contribuir, entre outros, para facilitar o acesso à informação e educação das pessoas com baixa literacia. Este estudo surge na sequência de um trabalho prévio que incluiu a anotação dos registos de vídeo de uma experiência com utilizadores realizada anteriormente. Com base na versão preliminar de análise do trabalho anterior, foi proposto um esquema de classificação de eventos que engloba tipos de interação relativos ao navegador, motor de pesquisa e páginas web. Cada tipo de interação é composto por eventos que, por sua vez estão associados a variáveis de análise. Dentro deste esquema, foram construídos módulos para analisar as interrogações de pesquisa submetidas. Com base neste esquema, foi revista a anotação dos vídeos e foi realizada a análise de dados de forma descritiva e inferencial. Os principais resultados demonstram que o grupo de baixa literacia em saúde utilizou sobretudo a caixa do motor de pesquisa e a funcionalidade de voltar atrás; interagiu mais tempo com página de resultados do motor de pesquisa, clicando mais com o botão esquerdo do rato e fazendo scrolling. Por outro lado, o grupo de alta literacia em saúde utilizou mais a barra de endereço e a funcionalidade de selecionar o texto do URL. Na página de resultados do motor de pesquisa este grupo fez mais cliques com o botão direito. A nível de reformulação de interrogações, que ocorrem no contexto da mesma necessidade de informação, os utilizadores com baixa literacia em saúde usaram mais as reformulações "totalmente novas", ou seja, sem termos em comum com a interrogação anterior. Por sua vez, o grupo de alta literacia em saúde fez mais reformulações.Health Literacy is "the level by which individuals can obtain, process, understand and communicate health-related information necessary to make informed health decisions". Users with a low level of health literacy are less aware of their medical conditions, more difficult to follow instructions and understand doctors' information. Increasingly, people turn to the web to search for health information. Low literacy users' difficulties in the real world are likely to continue to exist in the virtual world. The main objective of this study is to analyze the search behavior of users with different levels of health literacy. It intends to identify differences between people with low and high health literacy that can then be used to improve retrieval systems and contribute, among others, to facilitate access to information and education by people with low literacy. This study follows a previous work that included annotating video records of experience with users previously carried out. Based on the preliminary analysis version of the previous work, an event classification scheme was proposed that includes types of interactions related to the browser, search engine, and web pages. Each type of interaction is composed of events that, in turn, are associated with analysis variables. Within this scheme, modules were built to analyze the formulation of search queries. Based on this scheme, the annotation of the videos was revised, and the data analysis was performed in a descriptive and inferential manner. The main results demonstrate that the low health literacy group used mainly the search engine box and the backward feature. On the search engine results page, they clicked more with the left mouse button. On the results page, they spent more time on the interaction, mainly scrolling. On the other hand, the high health literacy group made more use of the address bar and the functionality of selecting the URL text. On the search engine results page, this group made more right-clicks. At the level of reformulations, which occur in the context of the same need for information, users with low health literacy used more "totally new" reformulations, that is, without terms in common with the previous question. In turn, the high health literacy group did more reformulations
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