4,040 research outputs found
The lifecycle of provenance metadata and its associated challenges and opportunities
This chapter outlines some of the challenges and opportunities associated
with adopting provenance principles and standards in a variety of disciplines,
including data publication and reuse, and information sciences
The Effects of the Quantification of Faculty Productivity: Perspectives from the Design Science Research Community
In recent years, efforts to assess faculty research productivity have focused more on the measurable quantification of academic outcomes. For benchmarking academic performance, researchers have developed different ranking and rating lists that define so-called high-quality research. While many scholars in IS consider lists such as the Senior Scholar’s basket (SSB) to provide good guidance, others who belong to less-mainstream groups in the IS discipline could perceive these lists as constraining. Thus, we analyzed the perceived impact of the SSB on information systems (IS) academics working in design science research (DSR) and, in particular, how it has affected their research behavior. We found the DSR community felt a strong normative influence from the SSB. We conducted a content analysis of the SSB and found evidence that some of its journals have come to accept DSR more. We note the emergence of papers in the SSB that outline the role of theory in DSR and describe DSR methodologies, which indicates that the DSR community has rallied to describe what to expect from a DSR manuscript to the broader IS community and to guide the DSR community on how to organize papers for publication in the SSB
Off the Beaten Path: Let's Replace Term-Based Retrieval with k-NN Search
Retrieval pipelines commonly rely on a term-based search to obtain candidate
records, which are subsequently re-ranked. Some candidates are missed by this
approach, e.g., due to a vocabulary mismatch. We address this issue by
replacing the term-based search with a generic k-NN retrieval algorithm, where
a similarity function can take into account subtle term associations. While an
exact brute-force k-NN search using this similarity function is slow, we
demonstrate that an approximate algorithm can be nearly two orders of magnitude
faster at the expense of only a small loss in accuracy. A retrieval pipeline
using an approximate k-NN search can be more effective and efficient than the
term-based pipeline. This opens up new possibilities for designing effective
retrieval pipelines. Our software (including data-generating code) and
derivative data based on the Stack Overflow collection is available online
- …