Archives des mots-clés : Knowledge discovery

Bounded Rationality in Scholarly Knowledge Discovery

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Authors : Kristina Lerman, Nathan Hodas, Hao Wu

In an information-rich world, people’s time and attention must be divided among rapidly changing information sources and the diverse tasks demanded of them. How people decide which of the many sources, such as scientific articles or patents, to read and use in their own work affects dissemination of scholarly knowledge and adoption of innovation.

We analyze the choices people make about what information to propagate on the citation networks of Physical Review journals, US patents and legal opinions. We observe regularities in behavior consistent with human bounded rationality: rather than evaluate all available choices, people rely on simply cognitive heuristics to decide what information to attend to.

We demonstrate that these heuristics bias choices, so that people preferentially propagate information that is easier to discover, often because it is newer or more popular. However, we do not find evidence that popular sources help to amplify the spread of information beyond making it more salient.

Our paper provides novel evidence of the critical role that bounded rationality plays in the decisions to allocate attention in social communication.

URL : https://arxiv.org/abs/1710.00269

Knowledge discovery through text-based similarity searches for astronomy literature

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Author : Wolfgang Kerzendorf

The increase in the number of researchers coupled with the ease of publishing and distribution of scientific papers (due to technological advancements) has resulted in a dramatic increase in astronomy literature.

This has likely led to the predicament that the body of the literature is too large for traditional human consumption and that related and crucial knowledge is not discovered by researchers. In addition to the increased production of astronomical literature, recent decades have also brought several advancements in computer linguistics.

Especially, the machine aided processing of literature dissemination might make it possible to convert this stream of papers into a coherent knowledge set. In this paper, we present the application of computer linguistics techniques on astronomy literature.

In particular, we developed a tool that will find similar articles purely based on text content given an input paper.

We find that our technique performs robustly in comparison with other tools recommending articles given a reference papers (known as recommender system). Our novel tool shows the great power in combining computer linguistics with astronomy literature and suggests that additional research in this endeavor will likely produce even better tools that will help researchers cope with the vast amounts of knowledge being produced.

URL : https://arxiv.org/abs/1705.05840