[MUSIC] Hello everyone. Welcome to Big Data and Language. In the previous lecture we talked about the limitations of big data. So, today let's talk about future directions of big data. Are you ready? Let's get started. So, the potential improvements will be needed, in other words, development of the machines and technology may allow us with a variety of ways to access the data. For example, the development of new coding program may allow us with better skills of crawling, resulting in better data collection. And also there will be better performing computers to process for much larger amount of data. And spoken data can be converted to the text file by speaking recognition program. And also, analyzing sentence structure will be possible. We will be able to understand the context with only analysis. And there should be more accurate analysis methods for big data. For example, if big data is used with deep learning, it would provide better analysis than before. And also it's necessary to develop a mechanism that can analyze the context of individual data using machine learning. So machine learning could be meaningful and helpful to understand the big data and use the big data in linguistics. And also a big data analyzing tool will be developed, which determines the validity and importance of each piece of data and put is as a weight in the analysis. So, from now, big data analysis is limited to analyze the frequency or collocates of words. But in the future machines can understand a full text meaning of conversations. So, we can extract a more meaningful data. Maybe new applications would be necessary. So, notion of big data will be more common. So, more fields allow us big data for their development. So, for example hospitals will use big data of patients and study more to cure patients. And also, when we order something, big data can be collected and analyzed automatically. For instance, if you want to analyze lyrics data, that automated system collect lyrics data and conduct analysis for you. So, that would be great. You don't need to design all the specific things, too, for your research. And current distress and difficulties by citizens and young people would be predictable, we can collect source of data for practice of deep learning AIs. And in addition, it will be interesting to study language translates as more languages are becoming available. So, these days Google Translate is great, but not perfect, and also limited to certain language. But if we develop more translators for other languages, diverse languages, then that will be some kind of future directions that we can predict. One should give effort and designing more robust language on analytic program, in order to make this development. And the education for big data analysis should be encouraged widely. The increased support and investment is needed. And since the language reflects the values, cultures, and trends of the society through big data, we can analyze and predict changes in society. And after the data sets for most of the languages will be created. There will be a research to find some common features for all human languages to understand language in common. So we can find any general features across languages. And it could be used to help people learn, understand, and translate languages. In a connected route environment big data is used for predicting the user's behavior and lifestyle, and recommends to users. And we can make robots more like humans, including emotion, personality, cognition, and movement. So, if we use big data in a better way or a more accurate way, then we can develop the more like human being robots. And probably the data collection will be, we will recognize various kinds of text data, such as books or newspapers and use it as the source. And the companies can collect data about the current popular trends and the customer's wishes. And from the data collection one could develop a better program for collecting spoken data, which can possibly reflect emotions and connotations. And we will be able to get more data because of the popularity of IoTs. Therefore we are able to get more accurate results. And as the technology improves, it would be easier and cheaper to collect rich and meaningful data. For example with voice recognition‚, we can easily collect spoken data. But let's think about the privacy. In the previous ‚lecture we talked about the privacy issues. So, the value of big data will increase‚ so people will privatize their data, resulting in competitive relationship to get data. So, in other words, it will be harder to access the private data. Social regulations and norms that can adequately protect private areas must be created. So, there will be some rules, laws, or policies about the privacy to protect the data related to privacy. So, today we talked about the future directions of big data. And next time finally, it's time to conduct your own research. So, let me give you the guideline and the peer review. Thank you for your attention.
