Mobile Findex: Facilitating Information Access in Mobile Web Search with Automatic Result Clustering

Heimonen, Tomi

doi:10.1155/2008/680640

Cited by 12 publications

(23 citation statements)

References 25 publications

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“…MobileFindex [10] is a mobile search interface that uses automatically computed categories to narrow down the scope of search and improve the presentation of the search result. A user can refer an overview of the result set when specifying the category.…”

Section: B Mobile Search Assistancementioning

confidence: 99%

How Does Mobile Context Affect People's Web Search Behavior?: A Diary Study of Mobile Information Needs and Search Behaviors

Komaki

Hara

Nishio

2012

2012 IEEE 26th International Conference on Advanced Information Networking and Applications

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Mobile devices have become popular to access the information on-the-move. However, the physical restrictions of mobile devices such as display size and input capabilities and the changes of users' contexts may affect the users' information needs and search behaviors. In order to design a new search service which takes mobile users' situation into consideration, it is essential to understand search behaviors of mobile users in detail. In this work, we conducted a diary study using 26 participants in Japan, focusing on how mobile context affects users' information needs and search behaviors. In particular, we focus on detailed behaviors when users failed to find the information they needed. Our main findings include that user's search behaviors were affected not only by the information needs but also the place where the searches were conducted, which might be an important cue to design future mobile search services and applications.

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Section: B Mobile Search Assistancementioning

confidence: 99%

How Does Mobile Context Affect People's Web Search Behavior?: A Diary Study of Mobile Information Needs and Search Behaviors

Komaki

Hara

Nishio

2012

2012 IEEE 26th International Conference on Advanced Information Networking and Applications

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“…Credino [7] clustered SERs and organized the clusters into an expandable hierarchy, where the cluster labels were assigned as links to an SERP. Mobile Findex [8] utilized a clustering technique that grouped all SERs sharing a common term under the same label to make SERs more accessible to users.…”

Section: Mobile Web Searchmentioning

confidence: 99%

Improving Mobile Web Search by Clustering and Visualizing Search Engine Results

Alasmari

Zhou

Zhang

2015

Proceedings of the 17th International Conference on Human-Computer Interaction With Mobile Devices and Services Adjunct

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The search engine makes vast amounts of information available to mobile users. Despite increasing use of mobile search engines, the mobile web search remains ineffective mainly due to the intensive scrolling inherent in the current presentation of search engine results (SERs) on the small screen of handheld devices. In this study, we proposed to improve the presentation of mobile SERs through clustering and visualization. Based on the cognitive load theory and information foraging theory, we proposed hypotheses about the possible effects of visualization and synchronous presentation of SERs and their clusters on user search performance. To test the hypotheses, we implemented five mobile web search prototypes, and evaluated the prototypes by conducting lab experiments.

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“…A common technique is to categorize the search results and present just the categories at a high level [18,16]. Quicklinks [10] is another technique that provides more than just the website, but also the structure of the site so that a user can directly reach a particular portion of the site.…”

Section: Search Interfaces On Mobile Devicesmentioning

confidence: 99%

Two-stream indexing for spoken web search

Ajmera

Joshi

Mukherjea

et al. 2011

Proceedings of the 20th International Conference Companion on World Wide Web

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This paper presents two-stream processing of audio to index the audio content for Spoken Web search. The first stream indexes the meta-data associated with a particular audio document. The meta-data is usually very sparse, but accurate. This therefore results in a high-precision, low-recall index. The second stream uses a novel language-independent speech recognition to generate text to be indexed. Owing to the multiple languages and the noise in user generated content on the Spoken Web, the speech recognition accuracy of such systems is not high, thus they result in a low-precision, high-recall index. The paper attempts to use these two complementary streams to generate a combined index to increase the precision-recall performance in audio content search. The problem of audio content search is motivated by the real world implication of the Web in developing regions, where due to literacy and affordability issues, people use Spoken Web which consists of interconnected VoiceSites, which have content in audio. The experiments are based on more than 20,000 audio documents spanning over seven live VoiceSites and four different languages. The results suggest significant improvement over a meta-data-only or a speech-recognitiononly system, thus justifying the two-stream processing approach. Audio content search is a growing problem area and this paper wishes to be a first step to solving this at a large scale, across languages, in a Web context.

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Mobile Findex: Facilitating Information Access in Mobile Web Search with Automatic Result Clustering

Cited by 12 publications

References 25 publications

How Does Mobile Context Affect People's Web Search Behavior?: A Diary Study of Mobile Information Needs and Search Behaviors

How Does Mobile Context Affect People's Web Search Behavior?: A Diary Study of Mobile Information Needs and Search Behaviors

Improving Mobile Web Search by Clustering and Visualizing Search Engine Results

Two-stream indexing for spoken web search

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