Using sentiment analysis technique for analyzing Thai customer satisfaction from social media

With the rapidly increasing number of Thai online customer reviews available in social media and websites, sentiment analysis technique, also called opinion mining, has become an important task in the past few years.This technique aims to analyze people’s emotions, opinion, attitudes and sentiments.The classical approaches for opinion mining represents the reviews as bag-of-words as many words can be used to identify positive or negative feedbacks.This makes these methods work well with European language reviews which are segmented texts.However, these bag-of-word based methods face problem with Thai customer’s review which is non-segmented text, since Thai texts are formed as a long sequence of characters without word boundaries.Up to now, not much research conducted on sentiment analysis for Thai customer reviews.This paper proposes a sentiment analysis technique for Thai customer’s reviews.The proposed technique is based on the integration of Thai word extraction and sentiment analysis techniques for mining Thai customer’s opinion. To demonstrate the proposed technique, experimental studies on analyzing Thai customer’s reviews from social media are presented in this paper.The results show that the proposed method provides significant benefits for mining Thai customer’s opinion from social media

Comment analysis for product and service satisfaction from Thai customers' review in social network

In the last decade, the amount of social media usage has rapidly increased exponentially in Thailand.A huge amount of Thai online reviews and comments are available on social network every second.Because of this fact, comment analysis, also called sentiment analysis, has then become an essential task to analyze people’s emotions, opinion, attitudes and sentiments from the amount of these online posts. This paper proposed the technique for analyzing Thai customers’ comments or opinions about the products and services by counting the polarity words of the product and service domains.To demonstrate the proposed technique, experimental studies on analyzing Thai customers’ comments in the social media are presented in this paper. The comments are classified into neutral, positive or negative.The proposed technique benefits the business domain in guiding product improvement and quality of service.Hence, this paper also benefits the end-users in making a smart decision

Using hybrid technique: the integration of data analytics and queuing theory for average service time estimation at Immigration Service, Suvarnabhumi Airport

In the past few years, Thai tourism industry has become one of the big markets in the world that makes the number of air passenger has growth rapidly.The survey shows that 15,883,928 passengers arrived at Suvarnabhumi international airport, Thailand in 2015 which increase around 11% every year.Due to this reason, the airport needs to seek for effective strategies to operate an immigration service in order to avoid long waiting time.The effective immigration operation actually can gain passenger satisfaction. In addition, the fast immigration process provides the significant benefit for businesses in the airport because short immigration waiting time would be able to increase the purchase amount in shopping area.This paper aims to propose the hybrid method, the intregration of data analytics and queuing theory, for average service time estimation at the immigration unit, Suvarnabhumi airport. From the experimental study, the proposed technique can estimate the average service time, server utilization and average number of passengers in a queue based on the statistic of arrival passengers. The result shows that the number of opened counter and month are the factors to provide different results

Using graph algorithm and classification technique for finding an optimal bus route in time-dependent travel times

In the last decade, traffic jam has been regarded as a main problems for Bangkok.Most people selects a bus option for traveling because it is cheap and cover every area in Bangkok. However, they are suffering from the long hours in traffic jam especially in rush hour.They also cannot avoid this such jam as bus routes are fixed by Bangkok Mass Transit Authority (BMTA).This paper aims to propose a technique for finding an Optimal Bus Route in Time-Dependent Travel Times by using graph algorithm and data mining technique. The proposed technique is able to find a least spent travel time path between two nodes in a bus network with time-dependence.Graph algorithm is used to generate all possible paths to reveal the distances.Classification technique is then used to analysis traffic situation in different period of the time.By analysis traffic situation, date, time, week, month, location are used as a main factor for training process in classification technique.From the experimental studies, the proposed technique is able to show the best route from any given node to the final destination depending on the different period of the time.The proposed technique provides significant benefit for traveler to select the best bus route, which is short distance and fast, among generated route

Filtering spam mail in non-segmented languages using hybrid approach: the integration of stopword removal, n-gram extraction and classification techniques

Junk mail or spam mail has been regarded as a major problem in today’s world. The spam mail can lead to cybercrime that impacts all individuals and organization.Many people and businesses seek for spam mail prevention technique in order to protect their own data and computer system.The spam mails normally contain advertise products or services contents and also conveys viruses, malwares, spywares and so forth.Many people thought spam mails do not cause any damage. In fact, the spam mails made a management cost increased and resources will be used ineffectively.Therefore, verifying and filtering spam mails need to be taken into consideration. The objective of this paper is to introduce the hybrid approach, which combines three techniques including stop-word removal, n-gram extraction and data classification, for filtering spam emails and simplifies system development.The proposed hybrid approach can be widely applied for all different languages due to being language independent technique. To examine the approach, CSDMC2010 spam mail corpus comprising of 198 common emails, 202 spam mails, and 10 selective emails were used in experimental study.The results showed that the proposed technique enabled to monitor whether the email is spam with 93.2% accuracy.Hence, this hybrid approach could provide benefits for all users and organization to decrease the computer risk

A frequent max substring technique for Thai text indexing

This research details the development of a novel methodology, called the frequent max substring technique, for extracting indexing terms and constructing an index for Thai text documents. With the rapidly increasing number of Thai digital documents available in digital media and websites, it is important to find an efficient Thai text indexing technique to facilitate search and retrieval. An efficient index would speed up the response time and improve the accessibility of the documents. Up to now, not much research in Thai text indexing has been conducted as compared to more commonly used languages like English. The more commonly used Thai text indexing technique is the word inverted index, which is language-dependent (i.e. requires linguistic knowledge). This technique creates word document indices on document collection to enable an efficient keyword based search. However, when using the word inverted index technique, Thai text documents need to be parsed and tokenized into individual words first. Therefore, one of the main issues is how to automatically identify the indexing terms from the Thai text documents before constructing the index. This is because the syntax of Thai language is highly ambiguous and Thai language is non-segmented (i.e. a text document is written continuously as a sequence of characters without explicit word boundary delimiters). To index Thai text documents, most language-dependent indexing techniques have to rely on the performance of a word segmentation approach in order to extract the indexing terms before constructing the index. However, word segmentation is time consuming and segmentation accuracy is heavily dependent either on the linguistic knowledge used in the underlying segmentation algorithms, or on the dictionary or corpus used in the segmentation. It is for this reason that most language dependent indexing techniques are time consuming and require additional storage space for storing dictionary or corpus or manually crafted rules resource. Apart from the language dependant indexing techniques, some language-independent techniques have been proposed as an alternative indexing technique for Thai language such as the n-gram inverted index and suffix array approaches. These approaches are simple and fast as they are language-independent, and do not require linguistic knowledge of the language, or the use of a dictionary or a corpus. However, the limitation of these techniques is that they require more storage space for extracting the indexing terms and constructing the index. To address the above limitations, this thesis has developed a frequent max substring technique that uses language-independent text representation, which is computationally efficient and requires small storage place. The frequent max substring technique improves the performance in terms of construction time over the language-dependent techniques (i.e. the word inverted index) as this technique does not require text pre-processing tasks (i.e. word segmentation) in extracting the indexing terms before indexing can be performed. This technique also improves space efficiency compared to some existing language-independent techniques. This is achieved by retaining only the frequent max substrings, which are strings that are both long and frequently occurring, in order to reduce the number of insignificant indexing terms from an index. To demonstrate that the frequent max substring technique could deliver its performance, experimental studies and comparison results on indexing Thai text documents are presented in this thesis. The technique was evaluated and compared in term of indexing efficiency and retrieval performance. The results show that the frequent max substring technique is more computationally efficient when compared to the word inverted index, and also that it requires less space for indexing when compared to some language independent techniques. Additionally, this thesis shows that the frequent max substring technique has an advantage in terms of versatility, as it can also be combined with other Thai language dependent techniques to become a novel hybrid language-dependent technique, in order to further improve the indexing quality. This technique can also be used with a neural network to enhance non-segmented document clustering. The frequent max substring technique also has the flexibility to be applied to other non-segmented texts like the Chinese language and genome sequences in bioinformatics due to its language independency feature

COMMENT ANALYSIS FOR PRODUCT AND SERVICE SATISFACTION FROM THAI CUSTOMERS' REVIEW IN SOCIAL NETWORK

In the last decade, the amount of social media usage has rapidly increased exponentially in Thailand. A huge amount of Thai online reviews and comments are available on social network every second. Because of this fact, comment analysis, also called sentiment analysis, has then become an essential task to analyze people’s emotions, opinion, attitudes and sentiments from the amount of these online posts. This paper proposed the technique for analyzing Thai customers’ comments or opinions about the products and services by counting the polarity words of the product and service domains. To demonstrate the proposed technique, experimental studies on analyzing Thai customers’ comments in the social media are presented in this paper. The comments are classified into neutral, positive or negative. The proposed technique benefits the business domain in guiding product improvement and quality of service. Hence, this paper also benefits the end-users in making a smart decision