Conceptual Query Expansion and Visual Search Results Exploration for Web Image Retrieval

Hoque, Enamul; Strong, Grant; Hoeber, Orland; Gong, Minglun

doi:10.1007/978-3-642-18029-3_8

Cited by 9 publications

(12 citation statements)

References 16 publications

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“…Although query expansion has been studied in only a few instances within the context of Web image retrieval, those that have explored such techniques have shown them to be promising (Hoque, Strong, et al, 2011b;Myoupo, Popescu, Borgne, & Moëllic, 2009). Since query expansion can be an effective tool for promoting diversity and provide assistance in query refinement, it can be beneficial for image search.…”

Section: Query Expansion and Search Results Diversificationmentioning

confidence: 98%

“…In previous work, we have explained how our approach automatically discovers related concepts found in Wikipedia pertaining to an image search query, and retrieves images through a query expansion process (Hoque, Strong, Hoeber, & Gong, 2011b;Hoque, Hoeber, Strong, & Gong, 2011c). This results in a diversification of the image search results, covering a broad range of concepts when the query is ambiguous.…”

Section: Introductionmentioning

confidence: 97%

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CIDER: Concept-based image diversification, exploration, and retrieval

Hoque

Hoeber

Gong

2013

Information Processing & Management

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Section: Query Expansion and Search Results Diversificationmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 97%

CIDER: Concept-based image diversification, exploration, and retrieval

Hoque

Hoeber

Gong

2013

Information Processing & Management

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“…For example, van Zwol et al proposed a method for optimizing this trade-off by estimating a query model from the distribution of tags that favours the dominant sense of an image search query [7]. Our work takes a different approach, enhancing the diversity of image search results through concept-based query expansion [8], [2].…”

Section: Related Workmentioning

confidence: 96%

“…In previous research, we have presented a method for diversifying image search results using concept-based query expansion based on information derived from Wikipedia [2]. In this work, we have modified our approach such that the degree of diversification can be controlled, allowing us to evaluate the trade-offs between diversification and precision among the image search results.…”

Section: Introductionmentioning

confidence: 97%

“…In our research, we explore an alternate approach that generates a diversified set of images covering the various aspects of the query, under the expectation that at least one of the interpretations matches the searcher's intent. Providing interactive zoom and focus operation can allowing users to visually explore the image space as they seek relevant images [2].…”

Section: Introductionmentioning

confidence: 99%

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Evaluating the Trade-Offs between Diversity and Precision for Web Image Search Using Concept-Based Query Expansion

Hoque

Hoeber

Gong

2011

2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology

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Even though Web image search queries are often ambiguous, traditional search engines retrieve and present results solely based on relevance ranking, where only the most common and popular interpretations of the query are considered. Rather than assuming that all users are interested in the most common meaning of the query, a more sensible approach may be to produce a diversified set of images that cover the various aspects of the query, under the expectation that at least one of these interpretations will match the searcher's needs. However, such a promotion of diversity in the search results has the side-effect of decreasing the precision of the most common sense. In this paper, we evaluate this trade-off in the context of a method for explicitly diversifying image search results via concept-based query expansion using Wikipedia. Experiments with controlling the degree of diversification illustrate this balance between diversity and precision for both ambiguous and specific queries. Our ultimate goal of this research is to propose an automatic method for tuning the diversification parameter based on degree of ambiguity of the original query.

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Analysis of image search queries on the web: Query modification patterns and semantic attributes

Choi

2013

J Am Soc Inf Sci Tec

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This study investigated query modification patterns and semantic attributes in queries executed during user searches for images on the web. Its purpose was to identify whether query modification patterns were related to users' contextual factors and content sources as well as whether the patterns characterize the use of semantic attributes expressed in users' search queries in an interactive web-searching process. To this end, a collection of 970 image search queries executed by undergraduate students in a naturalistic setting was analyzed. The study's findings showed that query modification patterns were significantly associated with content sources. Among the types of query modification employed, "Reformulation" and "New" were the most frequently used. Terms related to format, object, or place associated with an image also were found to be frequently used in search queries. Terms referring to type or genre were the most frequent attributes in web image search queries, which suggests a change from previous findings of search queries in a professional context. Implications are discussed in terms of search assistants for web image searches and semantic annotation to improve image indexing.

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Conceptual Query Expansion and Visual Search Results Exploration for Web Image Retrieval

Cited by 9 publications

References 16 publications

CIDER: Concept-based image diversification, exploration, and retrieval

CIDER: Concept-based image diversification, exploration, and retrieval

Evaluating the Trade-Offs between Diversity and Precision for Web Image Search Using Concept-Based Query Expansion

Analysis of image search queries on the web: Query modification patterns and semantic attributes

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