Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The paper describes a novel approach to categorize users’ reviews according to the three Quality in Use (QU) indicators defined in ISO: effectiveness, efficiency and freedom from risk. With the tremendous amount of reviews published each day, there is a need to automatically summarize user reviews to inform us if any of the software able to meet requirement of a company according to the quality requirements.  implemented the method of Latent Semantic Analysis (LSA) and its subspace to predict QU indicators.  build a reduced dimensionality universal semantic space from Information System journals and Amazon reviews. Next,  projected set of indicators’ measurement scales into the universal semantic space and represent them as subspace. In the subspace,  can map similar measurement scales to the unseen reviews and predict the QU indicators. Our preliminary study able to obtain the average of Fmeasure, 0.3627.
['Wendy Tan Wei Syn', 'Bong Chih How', 'Issa Atoum']
I am writing a research paper on a idea Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews
[{"from": "human", "value": "I am writing a research paper on a idea Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The paper describes a novel approach to categorize users\u2019 reviews according to the three Quality in Use (QU) indicators defined in ISO: effectiveness, efficiency and freedom from risk. With the tremendous amount of reviews published each day, there is a need to automatically summarize user reviews to inform us if any of the software able to meet requirement of a company according to the quality requirements.  implemented the method of Latent Semantic Analysis (LSA) and its subspace to predict QU indicators.  build a reduced dimensionality universal semantic space from Information System journals and Amazon reviews. Next,  projected set of indicators\u2019 measurement scales into the universal semantic space and represent them as subspace. In the subspace,  can map similar measurement scales to the unseen reviews and predict the QU indicators. Our preliminary study able to obtain the average of Fmeasure, 0.3627."}]