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Machine Learning Techniques for Annotations of Large Financial Text Datasets

2019 | Americas Conference on Information Systems | Citations: 0
Authors: Roberts, Jesse; Volk, Matthias; Neumann, Robert; Turowski, Klaus

Abstract: Today, a number of automated methods exist to augment predictive models with an ... Expand

Abstract: Today, a number of automated methods exist to augment predictive models with annotations when working on huge collections of unstructured texts. One such method involves the use of machine learning techniques. This work seeks to investigate the use of those techniques for annotations on UIMA -a framework used for the analysis of unstructured data. By using the design science research methodology, an annotator pipeline is created as the main artifact. It takes news and blog articles as input and extracts entities, which are then annotated with a sentiment. Concurrently a demonstration is taking place, using a set of 12,480 gold annotated documents on German car manufacturers as training data. By harnessing a multitude of validations methods and machine learning algorithms, all results are thoroughly tested and evaluated. As a result, this work provides a blueprint for research into the use of UIMA and machine learning techniques for domain constrained datasets. Collapse

Semantic filters: Apache Solr

Topics: decision making blog Apache Solr

Methods: computational algorithm machine learning experiment support vector machine literature sample
Batch to Real-Time: Incremental Data Collection & Analytics Platform
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2017 | HICSS | Citations: 0
Authors: Aydin, Ahmet; Anderson, Ken

Abstract: Real-time data collection and analytics is a desirable but challenging feature t ... Expand

Abstract: Real-time data collection and analytics is a desirable but challenging feature to provide in dataintensive software systems. To provide highly concurrent and efficient real-time analytics on streaming data at interactive speeds requires a welldesigned software architecture that makes use of a carefully selected set of software frameworks. In this paper, we report on the design and implementation of the Incremental Data Collection & Analytics Platform (IDCAP). The IDCAP provides incremental data collection and indexing in real-time of social media data; support for real-time analytics at interactive speeds; highly concurrent batch data processing supported by a novel data model; and a front-end web client that allows an analyst to manage IDCAP resources, to monitor incoming data in real-time, and to provide an interface that allows incremental queries to be performed on top of large Twitter datasets. Collapse

Semantic filters: Apache Solr

Topics: Twitter Cassandra mobile application Redis Apache Solr

Methods: design artifact literature study data modeling
The Social Factory: Connecting People, Machines and Data in Manufacturing for Context-Aware Exception Escalation
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2017 | HICSS | Citations: 0
Authors: Kassner, Laura; Hirmer, Pascal; Wieland, Matthias; Steimle, Frank; Königsberger, Jan; Mitschang, Bernhard

Abstract: Manufacturing environments are socio-technical systems where people have to inte ... Expand

Abstract: Manufacturing environments are socio-technical systems where people have to interact with machines to achieve a common goal. The goal of the fourth industrial revolution is to improve their ﬂexibility for mass customization and rapidly changing production conditions. As a contribution towards this goal, we introduce the Social Factory: a social network with a powerful analytics backend to improve the connection between the persons working in the production environment, the manufacturing machines, and the data that is created in the process. We represent machines, people and chatbots for information provisioning as abstract users in the social network. We enable natural language based communication between them and provide a rich knowledge base and automated problem solution suggestions. Access to complex production environments thus becomes intuitive, cooperation among users improves and problems are resolved more easily. Collapse

Semantic filters: Apache Solr

Topics: social network knowledge repository open source social media smart factory

Methods: design artifact natural language processing chatbot literature study
A novel social media competitive analytics framework with sentiment benchmarks
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2015 | Information & Management | Citations: 30
Authors: He, Wu; Wu, Harris; Yan, Gongjun; Akula, Vasudeva; Shen, Jiancheng

Abstract: In today's competitive business environment, there is a strong need for business ... Expand

Abstract: In today's competitive business environment, there is a strong need for businesses to collect, monitor, and analyze user-generated data on their own and on their competitors’ social media sites, such as Facebook, Twitter, and blogs. To achieve a competitive advantage, it is often necessary to listen to and understand what customers are saying about competitors’ products and services. Current social media analytics frameworks do not provide benchmarks that allow businesses to compare customer sentiment on social media to easily understand where businesses are doing well and where they need to improve. In this paper, we present a social media competitive analytics framework with sentiment benchmarks that can be used to glean industry-specific marketing intelligence. Based on the idea of the proposed framework, new social media competitive analytics with sentiment benchmarks can be developed to enhance marketing intelligence and to identify specific actionable areas in which businesses are leading and lagging to further improve their customers’ experience using customer opinions gleaned from social media. Guided by the proposed framework, an innovative business-driven social media competitive analytics tool named VOZIQ is developed. We use VOZIQ to analyze tweets associated with five large retail sector companies and to generate meaningful business insight reports. Collapse

Semantic filters: Apache Solr

Topics: social media marketing intelligence Twitter social media site competitive advantage

Methods: natural language processing sentiment analysis language model survey experiment

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Found 4 articles

Machine Learning Techniques for Annotations of Large Financial Text Datasets

Batch to Real-Time: Incremental Data Collection & Analytics Platform

The Social Factory: Connecting People, Machines and Data in Manufacturing for Context-Aware Exception Escalation

A novel social media competitive analytics framework with sentiment benchmarks