Help for Faceted DBLP

Automatic Phrases

Since querying FacetedDBLP for a list of terms as 'or' query takes quite some time, we treat each query by default as a phrase query. Example: If you enter 'Semantic Web' as query term, we only search for publications containing the phrase 'Semantic Web' and do not return publications containing 'semantic' or 'web' only.
You can disable such automatically generated phrases by clicking this checkbox.

Syntactic Query Expansion

While generating the DBLP++ data, which is the basis of the FacetedDBLP search engines, we simultaneously get to know about a (limited) set of different writings for a particular keyword / keyphrase. By default, we utilize this knowledge to enhance the query with syntactically similar terms without the need for a time-consuming stemming of our whole database. For example, we can enhance the query 'ontology' with 'ontologies' or the query 'business process model' with 'business process modeling', 'business process modelling', and 'business process models'.
For such a so-called "syntactic query expansion", you have three options:

  1. Expand the whole phrase only
  2. Disable syntactic query expansion
  3. Expans each word of the search query separately

We currently limit such syntactic query expansion to the most popular 10 terms in the database.


Currently, the result list is ordered by matches, i.e. how often they query term is contained in the title, the abstract, the authors' names, the venue title, or the keywords. We are planning to provide a set of alternative sort options soon.

The GrowBag Facet

The GrowBag Facet allows to do two things (in case the result set of the query contains sufficiently many documents that are associated with author keywords):

  1. Assess the different research areas that are touched by the query
  2. Reorder the result list according to a selection of research areas (when you select one / several of the areas in the GrowBag facet)

The basic idea of the facet is to use hierarchically organized categorization systems (so-called GrowBag graphs) of author keywords to present a condensed view on the keyword space as determined by the result set of the query. As an example, let's consider a GrowBag graph contains the keywords 'Semantic Web', 'RDF', and 'OWL', and 'Semantic Web' is a super-concept of both 'RDF' and 'OWL'. If these three keywords occur in the result set of the query 5, 10, and 20 times, respectively, then all occurrences of those three keywords will be summarized under 'Semantic Web', i.e. the GrowBag facet will show 'Semantic Web (35/20%)' (assuming that there are 175 keyword occurrances in total).

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