# SentenceLDA- and ConNetClus-Based Heterogeneous Academic Network Analysis for Publication Ranking
## 2 Literature Review
### Heterogeneous Network  
The heterogeneous network was originally used in communication and belongs to a type of network. That network is composed of computers, systems, and network devices. In most cases, different protocols run on different applications or functions. The origin of heterogeneous networks can be traced back to the BARWAN (Bay Area Research Wireless Access Network) project initiated by the University of California in 1995. In [30] [PERSON], the leader of this project, integrated different types of networks that overlap each other to build a heterogeneous network to meet different types of business needs. It can be seen that heterogeneous networks are mostly used to study wireless communication technology. At present, many pieces of research have been established in the frontier direction of data mining, namely, heterogeneous information networks. This method of peeling off other objects and only caring about the relationship between the research objects simplifies ideas well, but it causes a significant loss of information. In today's complex network, there are many kinds and types of connections between objects. At this time, introducing the heterogeneous information network can mine the potential value of data without losing the relationship between objects. The heterogeneous network can be used to implement a collaborative filtering recommendation algorithm, search-ranking algorithm, abnormal data detection, and so on. [PERSON] et al. [31] introduced user and item attribute information and integrated the scoring matrix into the heterogeneous information network, which effectively improved the recommendation accuracy. [PERSON] et al. [32] considered using the heterogeneous features of a 3D model that interrelated co-clustering. This method used limited semantic information--which comes from multi-channel information--to build a heterogeneous semantic network, and then converted the heterogeneous semantic network to the semantic features of a 3D model. [PERSON] et al. [33] proposed an improved meta path-based collaborative filtering algorithm for weighted heterogeneous information networks. The method was evaluated with the extended MovieLens dataset, and experimental results showed that our approach outperformed several traditional algorithms and made the result of recommendation more accurate. [PERSON] et al. [34] used complex heterogeneous information network simulation experiments to detect abnormal data so that the algorithm had a high anti-interference ability. Reference [35] proposed a method of combining meta-path selection and user preference Top-k correlation query on heterogeneous information networks to measure the correlation between different types of objects. There are many different types of vertexes in a heterogeneous network, some of which are more important. Such vertexes often affect the structure and function of the network to a greater extent. In recent years, more and more people have been paying attention to the ranking method of vertex importance, not only because of the theoretical research significance of this method but also because of its strong practical application value [36] Among the ranking results-based algorithms, most of the current ranking functions are defined based on homogeneous networks, such as PageRank and HITS, and there are also some ranking algorithms based on heterogeneous networks, such as dual-type rankClus [37] multi-type netClus [38] and other algorithms [39] In sorting methods such as heterogeneous networks, the relationship between different types of objects and objects of the same type is important. By moving from a single homogeneous network level to the analysis of multiple types of heterogeneous network objects, the analysis of sorting algorithms is also transformed from a specific webpage to an object-oriented level of operation.