29,827 research outputs found
Clustering-Based Materialized View Selection in Data Warehouses
Materialized view selection is a non-trivial task. Hence, its complexity must
be reduced. A judicious choice of views must be cost-driven and influenced by
the workload experienced by the system. In this paper, we propose a framework
for materialized view selection that exploits a data mining technique
(clustering), in order to determine clusters of similar queries. We also
propose a view merging algorithm that builds a set of candidate views, as well
as a greedy process for selecting a set of views to materialize. This selection
is based on cost models that evaluate the cost of accessing data using views
and the cost of storing these views. To validate our strategy, we executed a
workload of decision-support queries on a test data warehouse, with and without
using our strategy. Our experimental results demonstrate its efficiency, even
when storage space is limited
NEXT LEVEL: A COURSE RECOMMENDER SYSTEM BASED ON CAREER INTERESTS
Skills-based hiring is a talent management approach that empowers employers to align recruitment around business results, rather than around credentials and title. It starts with employers identifying the particular skills required for a role, and then screening and evaluating candidatesβ competencies against those requirements. With the recent rise in employers adopting skills-based hiring practices, it has become integral for students to take courses that improve their marketability and support their long-term career success. A 2017 survey of over 32,000 students at 43 randomly selected institutions found that only 34% of students believe they will graduate with the skills and knowledge required to be successful in the job market. Furthermore, the study found that while 96% of chief academic officers believe that their institutions are very or somewhat effective at preparing students for the workforce, only 11% of business leaders strongly agree [11]. An implication of the misalignment is that college graduates lack the skills that companies need and value. Fortunately, the rise of skills-based hiring provides an opportunity for universities and students to establish and follow clearer classroom-to-career pathways. To this end, this paper presents a course recommender system that aims to improve studentsβ career readiness by suggesting relevant skills and courses based on their unique career interests
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