FACeTOR: cost-driven exploration of faceted query results

@article{Kashyap2010FACeTORCE,
  title={FACeTOR: cost-driven exploration of faceted query results},
  author={Abhijith Kashyap and Vagelis Hristidis and Michalis Petropoulos},
  journal={Proceedings of the 19th ACM international conference on Information and knowledge management},
  year={2010}
}
Faceted navigation is being increasingly employed as an effective technique for exploring large query results on structured databases. This technique of mitigating information-overload leverages metadata of the query results to provide users with facet conditions that can be used to progressively refine the user's query and filter the query results. However, the number of facet conditions can be quite large, thereby increasing the burden on the user. We present the FACeTOR system that proposes… 

Figures and Tables from this paper

Multi-Select Faceted Navigation Based on Minimum Description Length Principle
TLDR
This paper proposes a multi-select scheme where multiple suggested values can be selected at one step, and a selected value can be used to either retain or exclude the resources containing it.
Facet discovery for structured web search: a query-log mining approach
TLDR
This paper model the user faceted-search behavior using the intersection of web query-logs with existing structured data and presents an automated solution that elicits user preferences on attributes and values, employing different disambiguation techniques ranging from simple keyword matching, to more sophisticated probabilistic models.
Numerical Range Facets Partition: Evaluation Metric and Methods
TLDR
This paper introduces the new problem of numerical facet range partition and formally frame it as an optimization problem to enable quantitative evaluation and reuse of search log data and proposes an evaluation metric based on user's browsing cost when using the suggested ranges for navigation.
Towards a Soft Faceted Browsing Scheme for Information Access
TLDR
A probabilistic framework for modeling and solving the soft faceted browsing problem is proposed, and the framework is applied to study the case of facet filter selection in e-commerce search engines.
A Survey of Faceted Search
TLDR
This paper first analyzes the representative facet search models, then presents a general faceted search framework, and surveys the related methods and techniques, including facet term extraction, hierarchy construction, compound term generation and facet ranking.
Numerical Facet Range Partition: Evaluation Metric and Methods
TLDR
This paper introduces for the first time the research problem on numerical facet range partition and formally frame it as an optimization problem, and proposes an evaluation metric to be applied to search engine logs to enable quantitative evaluation of a partition algorithm.
User effort minimization through adaptive diversification
TLDR
It is shown that for different search tasks there is a different ideal balance of relevance and diversity, and an efficient approximate algorithm is proposed to select a near-optimal subset of the query results that minimizes the expected user effort.
Improving User Efficiency in Structured Data Exploration
TLDR
This dissertation takes a principled approach to user data exploration and proposes techniques that simplify access to large and complex structured and semi-structured databases and presents an auto-completion style query formulation interface, which enables users to augment keyword queries by adding structured conditions.
Query Expansion Based on Clustered Results
TLDR
This work proposes two efficient algorithms named iterative single-keyword refinement and partial elimination based convergence, respectively, which effectively generate a set of expanded queries from clustered results that provides a classification of the original query results.
Information Exploration in E-Commerce Databases
TLDR
Why users are not able to explore e-commerce databases is studied and nine add-on extensions are proposed to address five limitations in the query and result panel that deter exploratory search using faceted browsing.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 39 REFERENCES
Minimum-effort driven dynamic faceted search in structured databases
TLDR
This paper proposes minimum-effort driven navigational techniques for enterprise database systems based on the faceted search paradigm that dynamically suggest facets for drilling down into the database such that the cost of navigation is minimized.
Measure-driven Keyword-Query Expansion
TLDR
This paper proposes a new searching model, similar in spirit to faceted search, that enables the progressive refinement of a keyword-query result and employs surprising word co-occurrence patterns and (optionally) numerical user ratings in order to identify meaningful top-k query expansions.
An Approach to Integrating Query Refinement in SQL
TLDR
This paper presents a query refinement framework and an array of strategies for refinement that address different aspects of the problem, and demonstrates the effectiveness of the query refinement techniques proposed.
Beyond basic faceted search
This paper extends traditional faceted search to support richer information discovery tasks over more complex data models. Our first extension adds exible, dynamic business intelligence aggregations…
Efficient IR-Style Keyword Search over Relational Databases
Fast and effective query refinement
Query Refinement is an essential information retrieval tool that interactively recommends new terms related to a particular query. This paper introduces concept recall, an experimental measure of an…
Faceted metadata for image search and browsing
TLDR
An alternative based on enabling users to navigate along conceptual dimensions that describe the images is presented, which makes use of hierarchical faceted metadata and dynamically generated query previews.
Automatic Extraction of Useful Facet Hierarchies from Text Databases
TLDR
This paper presents an unsupervised technique for automatic extraction of facets useful for browsing text databases, and shows that its techniques produce facets with high precision and recall that are superior to existing approaches and help users locate interesting items faster.
Automatic categorization of query results
TLDR
This paper dynamically generates a labeled, hierarchical category structure that users can determine whether a category is relevant or not by examining simply its label; she can then explore just the relevant categories and ignore the remaining ones, thereby reducing information overload.
BioNav: Effective Navigation on Query Results of Biomedical Databases
TLDR
The BioNav system is presented, a novel search interface that enables the user to navigate large number of query results by organizing them using the MeSH concept hierarchy, and uses an intuitive navigation cost model to decide what concepts to display at each step.
...
1
2
3
4
...