The notion of diversity in graphical entity summarisation on semantic knowledge graphs

Abstract

Given an entity represented by a single node q in semantic knowledge graph D, the Graphical Entity Summarisation problem (GES) consists in selecting out of D a very small surrounding graph S that constitutes a generic summary of the information concerning the entity q with given limit on size of S. This article concerns the role of diversity in this quite novel problem. It gives an overview of the diversity concept in information retrieval, and proposes how to adapt it to GES. A measure of diversity for GES, called ALC, is defined and two algorithms presented, baseline, diversity-oblivious PRECIS and diversity-aware DIVERSUM. A reported experiment shows that DIVERSUM actually achieves higher values of the ALC diversity measure than PRECIS. Next, an objective evaluation experiment demonstrates that diversity-aware algorithm is superior to the diversity-oblivious one in terms of fact selection. More precisely, DIVERSUM clearly achieves higher recall than PRECIS on ground truth reference entity summaries extracted from Wikipedia. We also report another intrinsic experiment, in which the output of diversity-aware algorithm is significantly preferred by human expert evaluators. Importantly, the user feedback clearly indicates that the notion of diversity is the key reason for the preference. In addition, the experiment is repeated twice on an anonymous sample of broad population of Internet users by means of a crowd-sourcing platform, that further confirms the results mentioned above.

An architecture for the autonomic curation of crowdsourced knowledge

“…On the other hand, Google Knowledge Graph is a powerful, broad spectrum tool, whereas the Aviator ontology is topical in the field of careers, thus better suited to resolve specific queries. A study [44] of how knowledge diversity influences the retrieval of specific ontology data, in the presence of a size restriction, has a possible application for phase two of our platform. Link strengths may be used to define the distance between concepts, thus providing a metric to measure diversity.…”

“…In contrast, Aviator employs an ontology spanning over several career fields and offers a rich set of features (career graph navigation and editing, exploration history tracking, etc.). Knowledge graph contributions provide some visualisation of the underpinning ontology, yet are either too specific [7,44,49] or designed for too broad a domain of applications (Google Knowledge Graph) to match the flexibility (node expansion, community edits) and customisation (personal ontologies) of Aviator.…”

Diversity of editors and teams versus quality of cooperative work: experiments on wikipedia

“…Recently, diversity-awareness has gained increasing interest also in other information-related areas where the actual information need of a user is unknown and/or the user query is ambiguous so that a controlled level of diversity introduced to the results increases their quality. Examples range from databases (Vee et al 2008) to Web search (Agrawal et al 2009) or to the quite novel problem of graphical entity summarisation in semantic knowledge graphs (Sydow et al 2013). A recent work (Strzezek et al 2015) demonstrates that a controlled level of population diversity increases the performance of genetic algorithm for some hard optimisation problems.…”

“…Diversity has proved to play an important role in multiple fields of information sciences and applications such as: text summarisation, web search (Agrawal et al 2009), databases (Vee et al 2008), recommender systems and semantic entity summarisation (Sydow et al 2013). Recent research also indicates that diversity of population plays a positive role in evolutionary algorithms (Strzezek et al 2015) Our hypothesis studied in this article is that diversity of editors and teams is a factor that positively affects the quality of work in a virtual cooperative environments.…”

Does a “Renaissance Man” Create Good Wikipedia Articles?

“…(Vee et al, 2008)) to Web search (e.g. (Agrawal et al, 2009)) or very recently to the quite novel problem of graphical entity summarisation in semantic knowledge graphs (Sydow et al, 2013). From the open collaboration point of view, diversity can be considered from many perspectives, for example as a team diversity vs homogeneity or a single editors's diversity of interest vs specialisation.…”