# Dual-Track Lifelong Machine Learning-Based Fine-Grained Product Quality Analysis
## 6 Experiment
### Named-Entity Recognition and Fine-Grained Analysis for the Carrier  
Discovering new entities is also essential during knowledge mining. For instance, the phone is related to carriers, so finding the carriers from reviews is also crucial. Creating a list of carriers is one possible way, but there are always new carriers. Thus, it is necessary to discover carriers from reviews. Although new carriers are unknown, they have the same features as old carriers. When customers mention a carrier, they may complain about the SIM card or cell signal. One possible way to discover the carriers is to find the organization in the review about SIM cards and signals. Stanford CoreNLP [52] is used to annotate the organization. CoreNLP has a named-entity recognition function and it can annotate the organization. However, it can only recognize the organization name starting with the up case, such as \"AT&T\". If the input changes to lower case, such as \"AT&T\", CoreNLP cannot work. Table 13 lists the organizations recognized by CoreNLP. Although it has some mistakes, such as \"All\", \"Simple\", etc., it narrows the search scope. There are many correct carriers in the list, including \"AT&T\", \"Verizon\", \"Sprint\", \"MetroPCS\", \"Tracfone\", \"Comcast\", \"T-Mobile\", and \"Vodafone\", \"BT\". There are many typos or abbreviations for a name. For example, \"AT&T\" also called \"ATT\", and \"T-Mobile\" was written as \"TMobile\", and \"TMobil\". Using existing NER tools, such as CoreNLP, is efficient, but it only works for the apparent entity. If the entity is written in lowercase, CoreNLP cannot recognize it. Thus, this work also uses coordinating relationships to find new entities, if two entities belong to the same class and coordinating conjunction can connect them. Based on this idea, this work annotates sentences and records which entities are shown together with known carriers. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Word** & **Frequency** & **Word** & **Frequency** & **Word** & **Frequency** \\ \hline AT\&T & 123 & Verizon & 58 & Apple & 14 \\ SIM & 10 & ATT & 6 & \"Sprint & 5 \\ Amazon & 4 & MetroPCS & 3 & Tracfone & 2 \\ MetroPCS & 2 & Comcast & 1 & Metro & 1 \\ PCS & 1 & Motorola & 1 & Mobil & 1 \\ Kroger & 1 & Vodafone & 1 & S7 & 1 \\ Lightning & 1 & TMobil & 1 & Service & 1 \\ All & 1 & Carriers & 1 & Local & 1 \\ Simple & 1 & Mobile & 1 & BT & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 13: Named-entity recognition result by CoreNLP. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Word** & **Score** & **Freq** & **En** & **Word** & **Score** & **Freq** & **En** \\ \hline perfect & 4.71 & 22 & 0.32 & flawless & 4.6 & 8 & 0.41 \\ great & 4.57 & 7 & 0.44 & protective & 4.38 & 5 & 0.56 \\ amazing & 4.33 & 3 & 0.59 & bad & 1.71 & 4 & 0.62 \\ clear & 4.29 & 3 & 0.62 & scuff & 4.29 & 4 & 0.62 \\ big & 4.24 & 5 & 0.63 & sensitive & 4.23 & 3 & 0.65 \\ replacement & 2.38 & 2 & 0.65 & large & 4.23 & 2 & 0.65 \\ good & 4.07 & 11 & 0.68 & beautiful & 4.17 & 3 & 0.68 \\ damaged & 1.83 & 3 & 0.68 & smooth & 4.17 & 2 & 0.68 \\ freezing & 4.17 & 2 & 0.68 & intermittent & 4.0 & 2 & 0.76 \\ flickering & 2.0 & 2 & 0.76 & small & 4.0 & 2 & 0.76 \\ chip & 3.27 & 6 & 0.76 & defective & 2.14 & 6 & 0.79 \\ crack & 2.63 & 53 & 0.79 & scratch & 3.4 & 350 & 0.82 \\ delayed & 3.67 & 2 & 0.84 & faulty & 3.38 & 2 & 0.86 \\ replaced & 2.62 & 5 & 0.86 & unresponsive & 2.73 & 3 & 0.86 \\ popped & 3.38 & 2 & 0.86 & poor & 3.0 & 2 & 0.86 \\ original & 3.75 & 3 & 0.86 & broken & 2.67 & 11 & 0.89 \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Sentiment scores of screen-related words; “En” refers to “Entropy”. There are two carriers found by the coordinating relationship in Table 14. \"Cricket\" refers to \"Cricket Wireless\", but CoreNLP may regard it as a kind of sport. Although Google is an internet company, it has also \"Google Fi\", and many customers use it as a carrier. In addition, based on Table 15, \"TMObile\" and \"Version\" are \"T-Mobile\" and a type of \"Verizon\".