Recommendation sequence
Where is the knowledge map going
Rufus
It's good to know that professor chan is coming up with a new book of knowledge. Compared to the publication knowledge mapping: methods, practices and applications, published in 2019, the book has a number of updates on its content, particularly in chapters 8 and 9. These elements reflect the rapid advances in knowledge mapping theory and technology in recent years, as well as the fruitful work of the author team. I've been looking at this book for the first time. Here's a little personal thought on two of these topics - knowledge mapping reasoning and the integration of knowledge mapping。
The reasoning of knowledge mapping is an extremely important issue in the function of knowledge mapping services. Many of the important issues based on the knowledge map can be solved without reasoning. In the words of professor chen wah-chul, knowledge is acquired through “the learning of large samples by machines and the deduction of small samples by knowledge”. It's the main battleground of knowledge mapping. The book's chapter on “knowledge mapping reasoning” presents a variety of reasoning approaches based on knowledge mapping, including rules-based, home-based, map-based, expression-based, neuronet-based and so on. The diversity of knowledge itself, coupled with the diversity of human thinking, determines the diversity of reasoning and the diversity of reasoning. There are already enough mechanisms for intellectual reasoning in the book, and although space constraints make it difficult to exhaust all possible methods of intellectual drawing reasoning in open semantics, the most basic “three pieces” — rules reasoning, neural network reasoning and graphic reasoning — are in place. And i had this idea: "the three pieces are like the sea, land, air." the figure is “sea”, and the hundreds of millions of levels of “equivalent” of knowledge is the “sea” of knowledge elements. One layer after another, the deep-deep nervous network in the clouds, is called the "empty" mid-air. As for the rule reasoning that emphasizes one step at a time, it is the old cow on the “land” floor, which does not look so “modern”, but it remains in the actual reasoning. I am convinced that these “three pieces” are like the most basic chemical elements, which are constantly being “synthesized” by the cultivators of knowledge maps as the most innovative and effective new mechanisms of reasoning。
One chapter of the book is dedicated to “integration of knowledge maps”. If a mapping of knowledge in a given field is compared to human experts in that field, it is perfectly conceivable that: there were many complex questionnaires that could not or could not be resolved by an expert, and a good team of experts would greatly enhance the ability to solve problems. The same applies to knowledge mapping. In our view, this is not just the integration of big data, but rather of big knowledge, reflecting to some extent the cooperative spirit of knowledge mapping and learning human experts. But i'd like to add that, in addition to the integration of knowledge mapping, it is possible to consider the alignment of knowledge mapping (only one word). Instead of integrating into a giant map, it would maintain its independence and build a team to work in multi-graph cooperation. They each have their own strengths and can be divided between tasks, and cross-cutting issues or divergent views can be discussed and even debated, thus introducing multidimensional flexibility. In fact, the author introduced in chapter 9 the concept of a federal knowledge map based on block chains and knowledge values, which, although nearing the end of the book, is very important. The idea of “de-centreization” referred to therein is a central concept of “knowledge mapping”. The federal knowledge map can be broad and generalized, and if it is accompanied by the federal studies advocated by professor yang, it will be as strong as the tigers, with greater power. Not only do they use their knowledge to solve problems cooperatively, but they also protect their intellectual property rights and form the basis of a chain of knowledge blocks (a proposal i made at a recent international conference). Personally, i believe that, in a sense, the convergence of knowledge mapping will show a far-reaching theoretical and research value than the integration of knowledge mapping. I even look forward to the emergence of the “knowledge map community” (keyword: cooperation, protection and competition) that may be far more complex than the general “knowledge map federation”。
A common problem with multi-graph cooperation and multi-graph integration is that the structure, grammar, semantics and expressions of the profiles may vary considerably, leading to the dilemma of what is known as “root-and-duck talk”. In such cases, how can we work together? Don't worry! After all, it's like, "it's been a long time. It's been a long time." one of them came out with a lot of research, and it's slowly becoming different. After a while, they came out of high places, and they unified the different genres at a higher level. It is now in a period of great development of knowledge mapping and is also in a phase of “division”. New technologies are available and available. It's just that the "hundreds of the house" is not enough. In the case of the intellectual reasoning referred to above, the presentation and presentation of the various reasoning methods are found in the literature, but the literature comparing and analysing them is relatively lacking. In the last section of this chapter, the book contains a brief analysis and comparison of several reasoning strategies, which are key to inform knowledge map developers. But we are not satisfied with this, but we look forward to more in-depth theoretical analysis and application guidance. This is particularly evident with regard to the various lines of knowledge expression in some of today's knowledge maps, including some of the most prestigious mega-knowledge maps at the international level. We believe that, at the right time, an authoritative international academic institution will come forward to set standards, to pack up and to form one. Just like qin's six countries, the words, the wide distances, the unity。
The presentation of knowledge mapping techniques is very comprehensive. From the acquisition, expression and storage of knowledge, the construction and integration of maps, to the queries, questions, and reasoning of the mapping, a variety of special types of knowledge maps are presented, with a large view of content. These techniques should all have the corresponding algorithms and be embodied in procedures that are in the hands of different developers and that may not be the only ones addressing the same issue. Here i think of the sharing of the corresponding software tools (remunerated or unpaid). It is not only an individual, specific sharing, but also an integrated, systematic sharing. This is important for knowledge map developers. The time-consuming duplication of development has been saved and efforts can be focused on the development of new technologies. I take this opportunity to appeal to my colleagues to focus on the development of a common platform for knowledge mapping. They combine many of the functions of knowledge mapping, from development, management to application, as an important component of knowledge mapping engineering. At the same time, i would like to highlight a statement made by professor chen, author of this book: "we want to see a large-scale, open-source, allowed mass download (dump) knowledge map." professor chen believes that only such knowledge mapping can reflect the place and influence of our knowledge mapping technology in the world. I fully support that initiative。
Returning to the purpose of the book, i note that what the author has written in this book is essentially based on his own teaching materials, and that in the future it will be adjusted and enriched in the light of advances in knowledge mapping disciplines. This is the path of light which teaches each other. We wish professor chan success
