-
Monchaux, S.; Amadieu, F.; Chevalier, A.; Mariné, C.: Query strategies during information searching : effects of prior domain knowledge and complexity of the information problems to be solved (2015)
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- Abstract
- This study addresses the impact of domain expertise (i.e. of prior knowledge of the domain) on the performance and query strategies used by users while searching for information. Twenty-four experts (psychology students) and 24 non-experts (students from other disciplines) had to search for psychology information from the Universalis website in order to perform six information problems of varying complexity: two simple problems (the keywords required to complete the task were provided in the problem statement), two more difficult problems (the keywords required had to be inferred) and two impossible problems (no answer was provided by the website). The results showed that participants with prior knowledge in the domain (experts in psychology) performed better (i.e. reached more correct answers after shorter search times) than non-experts. This difference was stronger as the complexity of the problems increased. This study also showed that experts and non-experts displayed different query strategies. Experts reformulated the impossible problems more often than non-experts, because they produced new queries with psychology-related keywords. The participants rarely used thematic category tool and when they did so this did not enhance their performance.
- Date
- 25. 1.2016 18:46:22
-
Lykke, M.; Price, S.; Delcambre, L.: How doctors search : a study of query behaviour and the impact on search results (2012)
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- Abstract
- 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.
-
Abacha, A.B.; Zweigenbaum, P.: MEANS: A medical question-answering system combining NLP techniques and semantic Web technologies (2015)
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- Abstract
- The Question Answering (QA) task aims to provide precise and quick answers to user questions from a collection of documents or a database. This kind of IR system is sorely needed with the dramatic growth of digital information. In this paper, we address the problem of QA in the medical domain where several specific conditions are met. We propose a semantic approach to QA based on (i) Natural Language Processing techniques, which allow a deep analysis of medical questions and documents and (ii) semantic Web technologies at both representation and interrogation levels. We present our Semantic Question-Answering System, called MEANS and our proposed method for "Answer Search" based on semantic search and query relaxation. We evaluate the overall system performance on real questions and answers extracted from MEDLINE articles. Our experiments show promising results and suggest that a query-relaxation strategy can further improve the overall performance.
-
Yuan, X.; Belkin, N.J.: Investigating information retrieval support techniques for different information-seeking strategies (2010)
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- Abstract
- We report on a study that investigated the efficacy of four different interactive information retrieval (IIR) systems, each designed to support a specific information-seeking strategy (ISS). These systems were constructed using different combinations of IR techniques (i.e., combinations of different methods of representation, comparison, presentation and navigation), each of which was hypothesized to be well suited to support a specific ISS. We compared the performance of searchers in each such system, designated experimental, to an appropriate baseline system, which implemented the standard specified query and results list model of current state-of-the-art experimental and operational IR systems. Four within-subjects experiments were conducted for the purpose of this comparison. Results showed that each of the experimental systems was superior to its baseline system in supporting user performance for the specific ISS (that is, the information problem leading to that ISS) for which the system was designed. These results indicate that an IIR system, which intends to support more than one kind of ISS, should be designed within a framework which allows the use and combination of different IR support techniques for different ISSs.
-
Cole, C.: ¬A theory of information need for information retrieval that connects information to knowledge (2011)
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- Abstract
- This article proposes a theory of information need for information retrieval (IR). Information need traditionally denotes the start state for someone seeking information, which includes information search using an IR system. There are two perspectives on information need. The dominant, computer science perspective is that the user needs to find an answer to a well-defined question which is easy for the user to formulate into a query to the system. Ironically, information science's best known model of information need (Taylor, 1968) deems it to be a "black box"-unknowable and nonspecifiable by the user in a query to the information system. Information science has instead devoted itself to studying eight adjacent or surrogate concepts (information seeking, search and use; problem, problematic situation and task; sense making and evolutionary adaptation/information foraging). Based on an analysis of these eight adjacent/surrogate concepts, we create six testable propositions for a theory of information need. The central assumption of the theory is that while computer science sees IR as an information- or answer-finding system, focused on the user finding an answer, an information science or user-oriented theory of information need envisages a knowledge formulation/acquisition system.
-
Grau, B.: Finding answers to questions, in text collections or Web, in open domain or specialty domains (2012)
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- Abstract
- This chapter is dedicated to factual question answering, i.e., extracting precise and exact answers to question given in natural language from texts. A question in natural language gives more information than a bag of word query (i.e., a query made of a list of words), and provides clues for finding precise answers. The author first focuses on the presentation of the underlying problems mainly due to the existence of linguistic variations between questions and their answerable pieces of texts for selecting relevant passages and extracting reliable answers. The author first presents how to answer factual question in open domain. The author also presents answering questions in specialty domain as it requires dealing with semi-structured knowledge and specialized terminologies, and can lead to different applications, as information management in corporations for example. Searching answers on the Web constitutes another application frame and introduces specificities linked to Web redundancy or collaborative usage. Besides, the Web is also multilingual, and a challenging problem consists in searching answers in target language documents other than the source language of the question. For all these topics, this chapter presents main approaches and the remaining problems.
-
Walhout, J.; Oomen, P.; Jarodzka, H.; Brand-Gruwel, S.: Effects of task complexity on online search behavior of adolescents (2017)
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- Abstract
- Evaluation of information during information problem-solving processes already starts when trying to select the appropriate search result on a search engine results page (SERP). Up to now, research has mainly focused on the evaluation of webpages, while the evaluation of SERPs received less attention. Furthermore, task complexity is often not taken into account. A within-subjects design was used to study the influence of task complexity on search query formulation, evaluation of search results, and task performance. Three search tasks were used: a fact-finding, cause-effect, and a controversial topic task. To measure perceptual search processes, we used a combination of log files, eye-tracking data, answer forms, and think-aloud protocols. The results reveal that an increase in task complexity results in more search queries and used keywords, more time to formulate search queries, and more considered search results on the SERPs. Furthermore, higher ranked search results were considered more often than lower ranked results. However, not all the results for the most complex task were in line with expectations. These conflicting results can be explained by a lack of prior knowledge and the possible interference of prior attitudes.
-
Xie, I.; Joo, S.: Factors affecting the selection of search tactics : tasks, knowledge, process, and systems (2012)
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- Date
- 29. 1.2016 19:02:38
-
Saastamoinen, M.; Järvelin, K.: Search task features in work tasks of varying types and complexity (2017)
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- Abstract
- Information searching in practice seldom is an end in itself. In work, work task (WT) performance forms the context, which information searching should serve. Therefore, information retrieval (IR) systems development/evaluation should take the WT context into account. The present paper analyzes how WT features: task complexity and task types, affect information searching in authentic work: the types of information needs, search processes, and search media. We collected data on 22 information professionals in authentic work situations in three organization types: city administration, universities, and companies. The data comprise 286 WTs and 420 search tasks (STs). The data include transaction logs, video recordings, daily questionnaires, interviews. and observation. The data were analyzed quantitatively. Even if the participants used a range of search media, most STs were simple throughout the data, and up to 42% of WTs did not include searching. WT's effects on STs are not straightforward: different WT types react differently to WT complexity. Due to the simplicity of authentic searching, the WT/ST types in interactive IR experiments should be reconsidered.
-
Aloteibi, S.; Sanderson, M.: Analyzing geographic query reformulation : an exploratory study (2014)
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- Date
- 26. 1.2014 18:48:22
-
Pontis, S.; Blandford, A.; Greifeneder, E.; Attalla, H.; Neal, D.: Keeping up to date : an academic researcher's information journey (2017)
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- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.1, S.22-35
-
Wu, I.-C.; Vakkari, P.: Effects of subject-oriented visualization tools on search by novices and intermediates (2018)
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- Date
- 9.12.2018 16:22:25
-
Sachse, J.: ¬The influence of snippet length on user behavior in mobile web search (2019)
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- Date
- 20. 1.2015 18:30:22
-
Hopkins, M.E.; Zavalina, O.L.: Evaluating physicians' serendipitous knowledge discovery in online discovery systems : a new approach (2019)
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- Date
- 20. 1.2015 18:30:22
-
Renugadevi, S.; Geetha, T.V.; Gayathiri, R.L.; Prathyusha, S.; Kaviya, T.: Collaborative search using an implicitly formed academic network (2014)
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- Date
- 20. 1.2015 18:30:22
-
Waschatz, B.: Schmökern ist schwierig : Viele Uni-Bibliotheken ordnen ihre Bücher nicht - Tipps für eine erfolgreiche Suche (2010)
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- Date
- 3. 5.1997 8:44:22
