با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
دسته بندی:
هوش تجاری - Business Intelligence
سال انتشار:
2015
عنوان انگلیسی مقاله:
Advanced topic modeling for social business intelligence
ترجمه فارسی عنوان مقاله:
مدل سازی موضوعات پیشرفته برای هوش تجاری اجتماعی
منبع:
sciencedirect - elsevier - http://dx.doi.org/10.1016/j.is.2015.04.005
نویسنده:
Enrico Gallinucci, Matteo Golfarelli, Stefano Rizzi
چکیده انگلیسی:
Social business intelligence combines corporate data with user-generated content (UGC) to make decision-makers aware of the trends perceived from the environment. A key role in the analysis of textual UGC is played by topics, meant as specific concepts of interest within a subject area. To enable aggregations of topics at different levels, a topic hierarchy has to be defined. Some attempts have been made to address the peculiarities of topic hierarchies, but no comprehensive solution has been found so far. The approach we propose to model topic hierarchies in ROLAP systems is called meta-stars. Its basic idea is to use metamodeling coupled with navigation tables and with dimension tables: navigation tables support hierarchy instances with different lengths and with non-leaf facts, and allow different roll-up semantics to be explicitly annotated; meta-modeling enables hierarchy heterogeneity and dynamics to be accommodated; dimension tables are easily integrated with standard business hierarchies. After outlining a reference architecture for social business intelligence and describing the metastar approach, we formalize its querying expressiveness and give a cost model for the main query execution plans. Then, we evaluate meta-stars by presenting experimental results for query performances and disk space. Keywords: business intelligence, social media, user-generated content, multidimensional modeling
قیمت: رایگان
توضیحات اضافی:
تعداد نظرات : 0