“…Automatic methods that define new facets are helpful for the long tail of product categories. We have developed an automatic facet extraction algorithm [24] for a leading CSP in Italy, which could be used for platforms like Amazon or AliBaba, which have millions of users worldwide. Given a product category, our algorithm finds clusters of homogeneous values, each one corresponding to one facet.…”
Section: Motivating Scenariomentioning
confidence: 99%
“…A considerable amount of information published on the web, for example in eCommerce, is accessible through faceted interfaces, which let users filter query results and explore the information space [7,8,12,24,39]. Figure 1 shows an example of the Amazon user interface to filter books using the property values for author ({MiaSheridan, LaurannDohner , .…”
Section: Introductionmentioning
confidence: 99%
“…These approaches extract and cluster facet values that are deemed to belong to a common property. Some approaches extract clusters of facet values for a domain using data analytics techniques offline [6,19,24,38], while others extract clusters of facet values from search results [8,13,42]. Many facet extraction approaches provide hierarchical faceted search over large text collections [6,19,38,42], but they are seldom used in eCommerce.…”
Section: Introductionmentioning
confidence: 99%
“…Facet annotation problems with input ⟨D, ?p, V ⟩ are relevant in (at least) two scenarios: facet values are either extracted for a given domain (e.g., a product category without specific facets in an eCommerce application [24]) or from search results [13] that have been filtered by a category (e.g., results for the search "Harry Potter" restricted to the Book domain). In both scenarios, K B predicates annotate unknown facet properties.…”
Section: Introductionmentioning
confidence: 99%
“…We focus on the first scenario, which has motivated our work. By combining facet extraction [24] and facet annotation we further automate the facet definition process, and provide an end-to-end solution for the complex task of maintaining and creating facets in a CSP, which can operate in highly dynamic environments where novel products and categories appear at a fast pace [11]. In addition, the reuse of property URIs from a reference K B enables semantic annotations of faceted classifications in a CSP using, for example, RDFa markup [2], which supports the smart aggregation of product data and semantic search [33,35].…”
Faceted interfaces are omnipresent on the web to support data exploration and filtering. A facet is a triple: a domain (e.g., Book), a property (e.g., author , lanдuaдe), and a set of property values (e.g.,
“…Automatic methods that define new facets are helpful for the long tail of product categories. We have developed an automatic facet extraction algorithm [24] for a leading CSP in Italy, which could be used for platforms like Amazon or AliBaba, which have millions of users worldwide. Given a product category, our algorithm finds clusters of homogeneous values, each one corresponding to one facet.…”
Section: Motivating Scenariomentioning
confidence: 99%
“…A considerable amount of information published on the web, for example in eCommerce, is accessible through faceted interfaces, which let users filter query results and explore the information space [7,8,12,24,39]. Figure 1 shows an example of the Amazon user interface to filter books using the property values for author ({MiaSheridan, LaurannDohner , .…”
Section: Introductionmentioning
confidence: 99%
“…These approaches extract and cluster facet values that are deemed to belong to a common property. Some approaches extract clusters of facet values for a domain using data analytics techniques offline [6,19,24,38], while others extract clusters of facet values from search results [8,13,42]. Many facet extraction approaches provide hierarchical faceted search over large text collections [6,19,38,42], but they are seldom used in eCommerce.…”
Section: Introductionmentioning
confidence: 99%
“…Facet annotation problems with input ⟨D, ?p, V ⟩ are relevant in (at least) two scenarios: facet values are either extracted for a given domain (e.g., a product category without specific facets in an eCommerce application [24]) or from search results [13] that have been filtered by a category (e.g., results for the search "Harry Potter" restricted to the Book domain). In both scenarios, K B predicates annotate unknown facet properties.…”
Section: Introductionmentioning
confidence: 99%
“…We focus on the first scenario, which has motivated our work. By combining facet extraction [24] and facet annotation we further automate the facet definition process, and provide an end-to-end solution for the complex task of maintaining and creating facets in a CSP, which can operate in highly dynamic environments where novel products and categories appear at a fast pace [11]. In addition, the reuse of property URIs from a reference K B enables semantic annotations of faceted classifications in a CSP using, for example, RDFa markup [2], which supports the smart aggregation of product data and semantic search [33,35].…”
Faceted interfaces are omnipresent on the web to support data exploration and filtering. A facet is a triple: a domain (e.g., Book), a property (e.g., author , lanдuaдe), and a set of property values (e.g.,
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