The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In recent years advent of social networking services has created large amounts of data. Microblogging website is a kind of social network in which users share short messages with others. One of the most popular microblogging services is Twitter. Every day millions of people post their opinions and sentiments in this microblog. Due to the large numbers of tweets, finding new approaches to discover...
Case-Based Reasoning also known as CBR model has been widely used to solve the problem in various cases. This study aims to explain the implementation of K-Nearest Neighbor Algorithm in Case-Based Reasoning model. The research showed that KNN algorithm is suitable to be used in CBR model. The results of this study are to measure the accuracy level of automatic answer identity formation and search...
In today's world, recommendation systems are used to solve the problem of information overload in many areas allowing users to focus on important information based on their interests. One of the areas where such systems can play a major role is in helping students achieve their career goals by generating personalized job and skill recommendations. At present, there are many job posting websites providing...
With the advent of communication media, a large upheaval in the volume of text messages has been observed in recent years. Messages are exchanged by mobile phone users to facilitate the speedy exchange of information. However, some messages are not solicited in every situation. Delivery of irrelevant/spam messages in a particular scenario often leads to the frustration of users. Also, it is of utmost...
In past, even though there is a lot of research work is done in the field of recommendation systems, the researchers did not target user contexts while recommending the content to the end users. Traditional recommendation systems while dealing with applications considers only users and items, and do not incorporate user context when delivering recommendations to querying end users. Contextual information...
This study aimed to analyze the learning objectives of the higher education textbooks, according to verbs of intended learning outcomes which were set by the Quality Management of Institute of Statistical Studies and Research (ISSR), Cairo University, Egypt. This study provides a set of recommendations that will help to choose the best chapters of a textbook which is investigating the largest amount...
Requirements elicitation is the activity of identifying facts that compose the system requirements. One of the steps of this activity is the identification of information sources, which is a time-consuming task. Text documents are typically an important and abundant information source. However, their analysis to gather useful information is also time consuming and hard to automate. Because of its...
With the prevalence of mobile devices such as smartphones and tablets, the ways people access to the Internet have changed enormously. In addition to the information that can be recorded by traditional Web-based e-commerce like frequent online shopping stores and browsing histories, mobile devices are capable of tracking sophisticated browsing behavior. The aim of this study is to utilize users' browsing...
Many data mining techniques are used to extract the patterns from the text documents. But the challenge is using those updated patterns is still a open research issue. Most of the text mining methods generally uses the term based approaches. The main problems faced by the term based approaches is of polysemy and synonymy. This paper focuses on the implementation of an particular discovery way to discover...
The book discusses the history of the Islamic inventors have been widely published, but the history books that have been known so far are textual-based so the search process for the aspect of the place and time aspects of historical events are sequential. Surely it makes the reader difficulties when trying to examine the history based on place and time-based historical events. This paper proposed...
Citation recommendation is an interesting and significant research area as it solves the information overload in academia by automatically suggesting relevant references for a research paper. Recently, with the rapid proliferation of information technology, research papers are rapidly published in various conferences and journals. This makes citation recommendation a highly important and challenging...
To explore the regularity of clinical medication of Gastro-esophageal reflux disease (GERD) through text mining approach. Literatures on GERD in SinoMed(Chinese biomedical literature service system) were collected. Results: BANXIA, CHAIHU and HUANGLIAN were commonly used Chinese herbs in sequence from high to low, the network of Chinese herbs, symptoms and patterns could be established. Conclusion:...
Sentiment analysis in text mining is known to be a challenging task. Sentiment is subtly reflected by the tone, affective state or emotion of a writer's expression in words. Conventional text mining techniques which are based on keyword frequency counting usually run short of accurately detecting such subjective information implied in the text. In this paper we evaluated several popular classification...
Machine learning techniques have the potential to alter the highly competitive online fashion retail industry by improving customer service through personalized recommendations. A fashion style classification system can improve the customer search functionality and provide a more personalized experience for the user. Supervised learning techniques with fashion based applications face the problem of...
This paper presents an improved method of selective ensemble to filter the spam messages. The design adopts clustering based on the diversity between sub-classifiers to solve the problem of selection. To improve accuracy and stability, a conception of confidence weight is proposed to evaluate the reliability of selected sub-classifiers. The training model is created with small datasets as in the real...
The vast numbers of digitised documents containing historical data constitute a rich research data repository. However, computational methods and tools available to explore this data are still limited in functionality. Research on historical archives is still largely carried out manually. Text mining technologies offer novel methods to analyse digital content to identify various types of semantic...
Nowadays, personalization e-learning becomes one of the interesting issues in e-learning research that continues to grow. Many studies proposed different approach to deliver adaptive learning content according to learner's characteristics, needs, and preferences. The outcomes from studies are various too. In this paper, in order to get best approach in task deliver learning content, preliminary study...
Spamming is becoming a major threat that negatively impacts the usability of e-mail. Although lots of techniques have been proposed for detecting and blocking spam messages, Spammers still spread spam e-mails for different purposes such as advertising, phishing, adult and other purposes and there is not any complete solution for this problem. In this work we present a novel solution toward spam filtering...
Text data are a major type of data in the modern society. Literatures have pointed out that more than 80% of data are in text form. It is important to study the insights from text data in addition to quantitative data. The development of text mining techniques started in the early 80's. The methodology has become much more mature in the recent years. In this article, we conduct a case study using...
This paper aims to design a system model that analyzes the unstructured data inside the posts about electronic products on social networking websites. For the purposes of this study, posts on social networking websites have been mined and the keywords are extracted from such posts. The extracted keywords and the ontologies of electronic products and emotions form the base for the text-mining model...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.