Known‐Item Search: Variations on a Concept

Lee, Jin Ha; Renear, Allen H.; Smith, Linda C.

doi:10.1002/meet.14504301126

Cited by 20 publications

(20 citation statements)

References 18 publications

(36 reference statements)

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“…The user can then either choose a single file among Cand(q, F), or desist from choosing any file. In our analysis we make two important assumptions that are customary in the scope of knownitem search [Ogilvie and Callan 2003;Lee et al 2006;Macdonald and Ounis 2006], as follows.…”

Section: Queries and Answersmentioning

confidence: 99%

See 1 more Smart Citation

On ranking techniques for desktop search

Cohen

Domshlak

Zwerdling

2008

ACM Trans. Inf. Syst.

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Users tend to store huge amounts of files, of various formats, on their personal computers. As a result, finding a specific, desired file within the file system is a challenging task. This article addresses the desktop search problem by considering various techniques for ranking results of a search query over the file system. First, basic ranking techniques, which are based on various file features (e.g., file name, access date, file size, etc.), are considered and their effectiveness is empirically analyzed. Next, two learning-based ranking schemes are presented, and are shown to be significantly more effective than the basic ranking methods. Finally, a novel ranking technique, based on query selectiveness, is considered for use during the cold-start period of the system. This method is also shown to be empirically effective, even though it does not involve any learning.

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Section: Queries and Answersmentioning

confidence: 99%

“…We will mainly focus on "known item" queries, that is, files that the user knows to exist and whose names the user can also recognize [Ogilvie and Callan 2003;Lee et al 2006;Macdonald and Ounis 2006]. In particular, we consider files that would normally be created or saved by the user, that is, excluding emails.…”

Section: Introductionmentioning

confidence: 99%

On ranking techniques for desktop search

Cohen

Domshlak

Zwerdling

2008

ACM Trans. Inf. Syst.

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“…According to cognitive psychology, there are some rules on user memory, which play an important role in managing PDS [12], [13], [14], [15]. For example, different from web search, PDS searches are known-item search, which means the user knows the existence of the searched items, and only want to relocate them for reuse.…”

Section: A Related Workmentioning

confidence: 99%

Exploring Personal CoreSpace for DataSpace Management

Meng

2009

2009 Fifth International Conference on Semantics, Knowledge and Grid

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Abstract-With rapid increment of personal data amount, how to efficiently search Personal DataSpace(PDS) becomes an interesting and promising research topic. Popular methods include folder explorer, desktop search tools, and etc. Because these methods ignore user features, they fail to work well in some cases. For example, sometimes users expect to relocate a personal document based on some fuzzy memory clues, such as its type, access time, and so on. These queries can't be supported well by current personal data management tools.The aim of this paper is to discover effective methods to help users search Personal DataSpace. We take Semantic Link Network(SLN) to describe PDS, and divide the semantic links of PDS into two classes: Objective Semantic Link(OSL) and Memory-based Semantic Link(MSL). Base on MSL, we propose a concept Personal CoreSpace(PCS), which is a classification view of personal resources and is specified as a n-dimensional space based on Resource Space Model(RSM). Furthermore we design an ontology of PCS based on user behavior features, and propose a method to design facet search interfaces for users to explore PCS efficiently. We validate the effectiveness of our methods by implementing a prototype system for PCS exploring.

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“…A score that aims at rewarding minimized search time and maximized accuracy is used to measure performance. Tasks are so-called Known Item Search (KIS) [5]: a visual one, where a 30 second video clip is played and then has to be found in the database, and a textual one, where the goal is to find an event that is specified by a textual description. An upper time limit for solving each KIS task exists.…”

Section: Introductionmentioning

confidence: 99%

Human-Based Video Browsing - Investigating Interface Design for Fast Video Browsing

Hürst

Werken

2015

2015 IEEE International Symposium on Multimedia (ISM)

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The Video Browser Showdown (VBS) is an annual event where researchers evaluate their video search systems in a competitive setting. Searching in videos is often a two-step process: first some sort of pre-filtering is done, where, for example, users query an indexed archive of files, followed by a human-based browsing, where users skim the returned result set in search for the relevant file or portion of it. The VBS aims at this whole search process, focusing in particular on its interactive aspects. Encouraged by previous years' results, we created a system that purely addresses the latter issue, i.e., interface and interaction design. By eliminating all kind of video indexing and query processing, we were aiming to demonstrate the importance of good interface design for video search and that its relevance is often underestimated by today's systems. This claim is clearly proven by the results our system achieved in the VBS 2015 competition, where our approach was on a par with the top performing ones. In this paper, we will describe our system along with related design decisions, present our results from the VBS event, and discuss them in further detail. Video browsing, video search interfaces, interaction design

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Known‐Item Search: Variations on a Concept

Cited by 20 publications

References 18 publications

On ranking techniques for desktop search

On ranking techniques for desktop search

Exploring Personal CoreSpace for DataSpace Management

Human-Based Video Browsing - Investigating Interface Design for Fast Video Browsing

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