网范文：“Information Technology Between Syntactic and Semantic Textual work ” 网络图建模是一个不错的选择,略论巨大的文本数据的能力，来降低数据的维数，文本可以被视为单词和短语之间的句法和语义概念。这篇计算机范文讲的是创新的影响。模型是实现观察的方式，英语论文范文，通过一定信息技术的实现，略论概述一些见解。其实关于这种创意无处不在，英语毕业论文，对于过去和目前的集体思维方式,创新使社会中的思想演变,包括社会、经济、甚至政治生活。连接他们之间的新想法,产品,甚至商业和创业平台。
还有一些政府机构,大企业在印尼，为了提高创新，全国创新者提交他们的建议，例如在陪审团面前的选择是数以百计的选择建议。集体的思想领域的创新是有用的。下面的范文讲述了这一问题。
Abstract
work and graph model is a good alternative to analyze huge collective textual data for the ability to reduce the dimensionality of the data. Texts can be seen as syntactic and semantic network among words and phrases seen as concepts. The model is implemented to observe the proposals of Indonesian innovators for implementation of information technology. From the analysis some interesting insights are outlined.
Keywords: innovation, semantic map, corpus, complex network, computational linguistics
Introduction
Innovation is said not about ideas, but more about recognition of ideas [2]. Ideas are everywhere in the past and current way of collective thinking, but innovation makes the direction of how ideas evolve within the society, be it social, economic, and even political life [15]. Thus, seeing innovation is like the best way to hover around the current living dots of ideas and the way people innovate is connecting them one another by the celebration of new ideas, products, and even business and entrepreneurial platforms. Along with some governmental institutions, there are some big corporations in Indonesia right now making a sort of “incubation” for new start-ups and young entrepreneurs in order to boost innovations in the country. They do the selections and the elected start-ups will be groomed in to the established business funded by investment. Before the selection phase, innovators around the country submit their proposal due to ideas, products, or even an ongoing business venture they were doing. In front of the jury for selection is hundreds of proposals to choose.
Whatever the new innovators stated in their proposals are collectively the field of ideas of innovations among current Indonesian people. The proposals can be seen as a collection of corpus reflecting the need of innovative ideas among the society. Reading them one by one in details is one way to get the insight, but seeing it visually by statistically data crunching is one alternative way to get the big picture. There are interesting patterns and properties by observing collection of texts as network and graph [14]. Graph representation can reduce the dimensionality of the text collections to gain insights instantaneously [5], thanks to the computational processing analysis.
work representation, widely known as semantic mapping, may reveal some interesting patterns represented by the corpus[3], not to mention that in some cases, gazing through the network visualizations may make people easier and faster to grasp interesting information within the corpus, rather than reading text by text. To discuss about the information revealed within the large corpus of innovator’s proposal is the main motivation of this . First, we discuss about the methodology review and acquisitions for textual analysis followed by general statistical properties of the collections of more than 300 proposals submitted by innovators in Indonesia to the National Telecommunication Company hosting the business incubation*) . Then the analysis delivers to the result and the discussions about the “face” of innovation related to information technology in Indonesia. The trends and major focus among Indonesian innovators brings the later discussions.
work of Text
Conventionally, semantic graphs are built from the relations parsed from corpus. Computationally speaking, there is a database of relational semantic concepts or key phrases that is used to “read” the observed text or document [7]. However, the used an alternative different way to see textual documents. It is interesting to see that textual network representation can be seen in two perspective on corpus. We could build the graph representation either by seeing the syntactic relations of concept, words, or phrases and the semantic relations among concepts based on a relational database [10].
While semantic analysis tries to capture the semantic structure within sentences, the syntactic one is built by connecting words (and phrases) in sentences into an integrated whole. The latter concerns more about the emerged patterns among words and phrases while not necessarily the conceptual represented by the words (and phrases). The idea of textual network representation presented in the is, nonetheless beyond the two distinctions. Words (and phrases) of which not grammatically sensitive (mostly nouns representing concepts) from each proposal document submitted for the refereeing process for the Incubation of Information Technology Innovation, are listed and modeled as fully connected graph of concepts.
From the yielded syntactic networks, we are also curious with the semantic-type network. We do this by reducing some edges to have a simpler image of the graph. To do this we use the minimum spanning tree algorithm [4]. This algorithm yield a mucho simpler network with tree representation: there is no closed loop within the network. Figure 1(b) illustrates the yielded semantic network. The statistical properties of the textual network gives the signature of complexity, it has similarity with the social network. The semantic network is statistically sparse with small 5 amount of nodes have a relations with the vast majority of other nodes, has high local clustering, low average distances among nodes, and the power law degree distribution [16]. The specific statistical stylized facts of the network from Indonesian language is discussed in detail in [14] and is not main the motivation of this .
Reading by Drawing Indonesian Innovation Profile
The result of the graph drawing after reading the more than 300 proposals submitted for Information Technology Incubation for the year 2017 is shown in syntactic graph (in figure 2) and semantic graph (figure 3) via the minimum spanning algorithm. The graphs are made of 2687 conceptual words/phrases. It is a huge number of concepts, but in both figures we resize the label of the nodes proportional due to the respective degree within the network. All of the submitted proposals are actually can be categorized within 9 basic classifications, namely, innovation in the theme of public service, education, digital media entertainment, 8 digital advertising, finance and banking, health applications, tourism applications, and transportation and logistics issues. However, there are only the first three categories are with highest number of applicants. Within the big three classifications, we do the similar calculations to see the most interesting and important issues as recognized and proposed by Indonesian innovators of information technology.
Discussions
The result of the analysis has delivered the semantic mapping of the major concerns in the realm of Indonesian innovators when they face the issue of information technology. Syntactic map in figure 2 shows a more like “word cloud” depicting the relations among the concepts and how one proposal is related to one another. The words “system”, “data” “mobile”, “applications”, “information”, and “web” are the most used words within all of the submitted proposals. However, when it comes to the more hierarchical representation (figure 3), we can see that the word “engagement”, “advertising”, and “knowledge” are the main course of the whole proposals collectively. When we contrasted this finding with the centrality measures within the network, we can see that most innovators were talking about things related to the 9 products, and some technical issue due to growing and establishing the informational infrastructures (e.g.: data, applications, features). A little bit different with the one can be measured in the semantic network which is more about “how to develop business with the information technology” as shown by the importance of business-related words/phrases like “advertising”, “cost”, “service and goods”, and so on.
Concluding Remarks
Simplicity out of complexity is an important issue when we talk about the huge textual documents. The employment of semantic network to map concepts (words and phrases) used in the corpus may help to do this. The network representation can potentially be used to reduce the dimensionality of large amount of texts into some particular levels in which we can have instantaneous understanding of the global properties and stylized facts within corpus. As we implement this into hundreds of proposals to for information-technology business incubation, we gain some important aspects due to the realms of Indonesian innovators in their endeavors for the acquisitions of information technology in specific domains, be it public services, education, entertainment, and so on. Most proposals for the acquisitions of information-technology are about how to administer business development. The variations among topics they propose has dimmed the technical and specific aspects of the information technology they want to focus on. However, by using the analyses with the domain-specific semantic network, we can reveal some important and central theme they want to deliver in area of public services, education, and digital entertainment.()
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