CN102136975B - Large-scale network environment-oriented similarity network construction method - Google Patents
Large-scale network environment-oriented similarity network construction method Download PDFInfo
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Abstract
本发明涉及一种面向大规模网络资源环境的相似网络构建方法，目的在于增强资源间链接的语义性，形成一个具有相似关系的语义虚拟层，改善目前网络资源的管理及网络服务的低效和不准确性。本方法首先利用分而治之的策略，把资源先粗糙的分为若干个较小的资源块，然后再在每个资源块中进一步细致的处理，降低直接于大规模资源中处理的复杂度；其次，构建一个三层的网络模型，包括资源层、话题层和社区层，保证构建网络的连通性；再次，构建反馈机制，分别位于话题层和社区层，使更多的资源融入构建的网络；最后，加入人机交互机制，让用户修正机器构建的相似网络的链接，使网络链接更符合人类思维。The invention relates to a similar network construction method for a large-scale network resource environment. The purpose is to enhance the semantics of links between resources, form a semantic virtual layer with similar relationships, and improve the management of current network resources and the inefficiency and inefficiency of network services. inaccuracy. This method first uses the strategy of divide and conquer, divides resources roughly into several smaller resource blocks, and then further detailed processing in each resource block, reducing the complexity of direct processing in large-scale resources; secondly, Construct a three-layer network model, including resource layer, topic layer and community layer, to ensure the connectivity of the network; thirdly, build a feedback mechanism, respectively located in the topic layer and community layer, so that more resources can be integrated into the constructed network; finally , adding a human-computer interaction mechanism, allowing users to modify the links of similar networks constructed by machines, so that network links are more in line with human thinking.
Description
Technical field
The present invention relates to a kind of similar network establishing method towards large-scale network resource environment, more specifically, relate to a kind ofly in the text resource of magnanimity, set up similar link to form the method for a similar network.
Background technology
Similar network is a semantic layer based on similarity relation organization network resource, aims to provide to have to enrich semantic network service, for example: network intelligence is browsed and intelligent search.But it is an impossible thing that the method for traditional similar network of structure is applied under the environment of large-scale network resource.Reason has two: one is high complexity computing time.Suppose to utilize to calculate between two and directly calculate similarity,, when resource extent is very large, Riming time of algorithm is the growth of resource extent quadratic term.Another reason is that the similar network link building is poor.While supposing to calculate, similarity threshold is got low, can guarantee to build the connectedness of network, but accuracy is just lower.And similarity threshold is got height, guaranteed accuracy and reduced connectedness.Present patent application is utilized a series of strategies and technology, has perfectly solved the problem on the organization and management that magnanimity resource brings.
Summary of the invention
The object of the invention is to the managerial difficulty that the magnanimity for the information on network causes, and the network service inefficiency and the inaccuracy that run into while providing, a kind of similar network establishing method towards large-scale network environment is provided, by the text resource link with similarity relation together, form a semantic virtual level with similarity relation.
For achieving the above object, design of the present invention is:
First, consider to utilize the strategy of dividing and rule, resource first coarse be divided into several less Resource Block, and then further careful processing in each Resource Block, reduces the complexity of directly processing in extensive resource;
Secondly, consider to build the network model of three layers, comprise resource layer, topic Ceng He community layer, guarantee to build the connectedness of network;
Again, consider to build feedback mechanism, lay respectively at topic Ceng He community layer, make more resource incorporate the network of structure;
Finally, consider to add man-machine interaction mechanism, allow user revise the link of the similar network of machine structure, make network linking more meet human thinking.
According to appeal inventive concept, the present invention adopts following technical proposals:
(1) thought based on acquaintance's immune algorithm, self adaptation is excavated network potential similarity community center;
(2) community center obtaining according to self adaptation, based on Boolean calculation, excavates the coarse similar community in large-scale network resource;
(3), based on matrix reasoning, excavate the topic center in similar community;
(4) according to obtained topic center, use the k-means algorithm of revising, form topic;
(5) build the similar network with Three Tiered Network Architecture, include community's layer, topic layer and resource layer;
(6) utilizing man-machine interaction mechanism to adjust in the similar network of having set up links.
The present invention compares with existing semantic interlink network establishing method, has following significant advantage: the present invention, towards large-scale network resource, adopts the strategy of dividing and rule generally, reduces the time complexity of direct construction.When excavating similar community, the selection of community center is subject to the inspiration of immune algorithm thought, and the similar community center of excavation is than the more high accuracy that has of choosing at random; The algorithm that has designed in addition Boolean calculation forms similar community, reduces the huge time loss that numerical operation brings.While producing different topic in coarse similar community, the center of topic is not some text resources, but that the method for utilizing matrix reasoning produces is more accurate, has that the frequent mode of the keyword of strong representation ability more forms, and be adaptive generation; In addition, utilize the thought of k-means algorithm to form topic, wherein added similarity threshold to avoid the text resource that similarity is lower to be grouped into the accuracy that has reduced plan structure network in some topics.Finally, structure be the similar network with Three Tiered Network Architecture, different layers is managed different level knowledge, meets knowledge hierarchy structure, and has increased network link.
Details are as follows for a preferred embodiment of the present invention:
This concrete implementation step towards the similar network establishing method of large-scale network environment is as follows:
(1) thought based on acquaintance's immune algorithm, self adaptation is excavated network potential similarity Web Community center.From resource collection, get at random a text, find some texts similarly, and extract the main contents of these texts as the center of potential similarity community.
(2) community center obtaining according to self adaptation, based on Boolean calculation, excavates the coarse similar community in large-scale network resource.The similar community center forming according to previous step, does logical “and” operation to similar community center one by one the Internet resources of magnanimity, and satisfactory resource division, in the similar community of correspondence, is formed to several coarse similar communities.
(3), based on matrix reasoning, excavate the topic center in similar community.Each excavation to coarse similar community by the form of matrix, represent, utilize matrix reasoning to excavate multinomial frequent mode, self adaptation forms different topic centers.Wherein defined matrix is: text resource of line display of matrix, and the corresponding keyword that forms text of row, if a text resource comprises certain keyword, in correspondence position set, on the contrary reset.And newly define a matrix operation operation
: every a line of previous matrix and each row of a rear matrix are done logic "and" operation, using the outcome record meeting the demands in matrix of consequence as the foundation of next step keyword Mining Frequent Patterns.If previous matrix is frontier, a rear matrix is later, and matrix of consequence is product,
the process of computing is:
(m, n represents respectively line number and the columns of matrix frontier, n, p represents respectively line number and the columns of matrix later)
Matrix
operation is to form potential topic center in order to excavate multinomial frequent item set.The formula of k item frequent mode is excavated in definition:
Wherein, matrix D is the matrix notation of a coarse similar community, D
tfor the transposed matrix of D,
record the matrix of consequence of k item Frequent Set.The last Candidate Set using the frequent item set excavating as the center of potential topic.
(4) according to obtained topic center, revise k-means algorithm, form topic.Similarity threshold is set, utilizes k-means method to form in each community and produce topic, in the topic that guarantees to form, do not include the text resource lower than similarity threshold.
(5) build the similar network with Three Tiered Network Architecture, include community's layer, topic layer and resource layer.Community's layer links all community centers; The core of all topics in topic layer link Yi Ge community; Internet resources in a topic of resource layer management.
(6) utilizing man-machine interaction mechanism to adjust in the similar network of having set up links.
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| EP2741249A1 (en) * | 2012-12-04 | 2014-06-11 | Alcatel Lucent | Method and device for optimizing information diffusion between communities linked by interaction similarities |
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| CN101369921A (en) * | 2008-09-12 | 2009-02-18 | 中国科学技术大学 | A method for generating self-similar network traffic |
| CN101571853A (en) * | 2009-05-22 | 2009-11-04 | 哈尔滨工程大学 | Evolution analysis device and method for contents of network topics |
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| CN101369921A (en) * | 2008-09-12 | 2009-02-18 | 中国科学技术大学 | A method for generating self-similar network traffic |
| CN101571853A (en) * | 2009-05-22 | 2009-11-04 | 哈尔滨工程大学 | Evolution analysis device and method for contents of network topics |
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