Development of technology for customer requirement-based reference design retrieval

Engineering design is a knowledge-intensive process, and includes conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each task involves various aspects of knowledge and experience. Whether this knowledge and experience can be effectively shared is key to increasing product development capability and quality, and also to reducing the duration and cost of the development cycle. Therefore, offering engineering designers various query methods for retrieving engineering knowledge is one of the most important tasks in engineering knowledge management.The study develops a technology for customer requirement-based reference design retrieval to provide engineering designers with easy access to relevant design and associated knowledge. The tasks involved in this research include (i) designing a customer requirement-based reference design retrieval process, (ii) developing techniques related to the technology for customer requirement-based reference design retrieval, and (iii) implementing a customer requirement-based reference design retrieval mechanism. The retrieval process comprises the steps of customer requirement-based query, case searching and matching, and case ranking. The technology involves (1) a structured query model for customer requirement, (2) an index structure for historical design cases, (3) customer requirement-based case searching and matching mechanisms, (4) a customer requirement-based case ranking mechanism, and (5) a case-based representation of designed entities.     

Developing a multi-layer reference design retrieval technology for knowledge management in engineering design

Engineering design is a knowledge-intensive process that encompasses conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each of these tasks involves various areas of knowledge and experience. The sharing of such knowledge and experience is critical to increasing the capacity for developing products and to increasing their quality. It is also critical to reducing the duration and cost of the development cycle. Accordingly, offering engineering designers various methods for retrieving engineering knowledge is one of the most important tasks in managing engineering knowledge.

This study develops a multi-layer reference design retrieval technology for engineering knowledge management to provide engineering designers with easy access to relevant design and related knowledge. The tasks performed in this research include (i) designing a multi-layer reference design retrieval process, (ii) developing techniques associated with multi-layer reference design retrieval technology, and (iii) implementing a multi-layer reference design retrieval mechanism. The retrieval process contains three main phases—‘customer requirement-based reference design retrieval’, ‘functional requirement-based reference design retrieval’ and ‘functional feature-based reference design retrieval’. This technology involves (1) customer requirement-based reference design retrieval, which involves a structured query model for customer requirements, a case-based representation of designed entities, a customer requirement-based index structure for historical design cases, and customer requirement-based case searching, matching and ranking mechanisms, (2) functional requirement-based reference design retrieval, which includes a structured query model for functional requirements, a functional requirement-based index structure for historical design cases, and functional requirement-based case searching, matching and ranking mechanisms, and (3) functional feature-based reference design retrieval, which is a binary code-based representation for functional features, an ART1 neural network for functional feature-based case clustering and functional feature-based case ranking.     

Developing a multi-layer reference design retrieval technology for knowledge management in engineering design

Engineering design is a knowledge-intensive process that encompasses conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each of these tasks involves various areas of knowledge and experience. The sharing of such knowledge and experience is critical to increasing the capacity for developing products and to increasing their quality. It is also critical to reducing the duration and cost of the development cycle. Accordingly, offering engineering designers various methods for retrieving engineering knowledge is one of the most important tasks in managing engineering knowledge.This study develops a multi-layer reference design retrieval technology for engineering knowledge management to provide engineering designers with easy access to relevant design and related knowledge. The tasks performed in this research include (i) designing a multi-layer reference design retrieval process, (ii) developing techniques associated with multi-layer reference design retrieval technology, and (iii) implementing a multi-layer reference design retrieval mechanism. The retrieval process contains three main phases—‘customer requirement-based reference design retrieval’, ‘functional requirement-based reference design retrieval’ and ‘functional feature-based reference design retrieval’. This technology involves (1) customer requirement-based reference design retrieval, which involves a structured query model for customer requirements, a case-based representation of designed entities, a customer requirement-based index structure for historical design cases, and customer requirement-based case searching, matching and ranking mechanisms, (2) functional requirement-based reference design retrieval, which includes a structured query model for functional requirements, a functional requirement-based index structure for historical design cases, and functional requirement-based case searching, matching and ranking mechanisms, and (3) functional feature-based reference design retrieval, which is a binary code-based representation for functional features, an ART1 neural network for functional feature-based case clustering and functional feature-based case ranking.     

Continuous improvement of knowledge management systems using Six Sigma methodology

Knowledge retrieval is a decisive part of the performance of a knowledge management system. In order to enhance retrieval accuracy, an effective performance evaluation mechanism is necessary. Nowadays, there is not a standard evaluation framework for knowledge retrieval evaluation, because the evaluation set up is still technology-dependent, focusing on specific elements of the search context. The laboratory-based evaluation is not suitable to evaluate the knowledge retrieval process, since knowledge is dynamic, constantly changing and evolving. Besides, ambiguous query is also an important factor for the performance of knowledge retrieval systems. In order to improve the performance of knowledge retrieval, this paper proposes an evaluation mechanism using Six Sigma methodology to help developers continuously control the knowledge retrieval process. Specifically, this study involves the following tasks: (i) proposes a general knowledge retrieval framework based on the analysis result of knowledge retrieval, (ii) designs the knowledge retrieval evaluation framework using Six Sigma's Define-Measure-Analyze-Improve-Control (DMAIC) process and (iii) develops the related technologies to implement the knowledge retrieval evaluation mechanism. The knowledge retrieval evaluation mechanism allows system developers to maintain the knowledge retrieval system with ease and meanwhile enhance the accuracy.     

Query Expansion for Effective Retrieval Results of Hindi–English Cross-Lingual IR

Information retrieval (IR) is the science of identifying documents or sub-documents from a collection of information or database. The collection of information does not necessarily be available in only one language as information does not depend on languages. Monolingual IR is the process of retrieving information in query language whereas cross-lingual information retrieval (CLIR) is the process of retrieving information in a language that differs from query language. In current scenario, there is a strong demand of CLIR system because it allows the user to expand the international scope of searching a relevant document. As compared to monolingual IR, one of the biggest problems of CLIR is poor retrieval performance that occurs due to query mismatching, multiple representations of query terms and untranslated query terms. Query expansion (QE) is the process or technique of adding related terms to the original query for query reformulation. Purpose of QE is to improve the performance and quality of retrieved information in CLIR system. In this paper, QE has been explored for a Hindi–English CLIR in which Hindi queries are used to search English documents. We used Okapi BM25 for documents ranking, and then by using term selection value, translated queries have been expanded. All experiments have been performed using FIRE 2012 dataset. Our result shows that the relevancy of Hindi–English CLIR can be improved by adding the lowest frequency term.     

双特征空间的实体排序学习

随着大规模知识图谱的出现以及企业高效管理领域知识图谱的需求,知识图谱中的自组织实体检索成为研究热点。给定知识图谱以及用户查询,实体检索的目标在于从给定的知识图谱中返回实体的排序列表。从匹配的角度来看,传统的实体检索模型大都将用户查询和实体统一映射到词的特征空间。这样做具有明显的缺点,例如,将同属于一个实体的两个词视为独立的。为此,该文提出将用户查询和实体同时映射到实体与词两个特征空间方法,称为双特征空间的排序学习。首先将实体抽象成若干个域。之后从词空间和实体空间两个维度分别抽取排序特征,最终应用于排序学习算法中。实验结果表明,在标准数据集上,双特征空间的实体排序学习模型性能显著优于当前先进的实体检索模型。     

The push strategy of product design knowledge in cloud environment with the multidimensional hierarchical context and SSA-BPNN model

To assist designers in completing design tasks and improve the efficiency of product design, more and more design knowledge push approaches are coming about. With developments of information technology and cloud computing, knowledge service goes with the whole design process and it is represented by the knowledge push forming. The knowledge push is complex engineering, however, existing knowledge push approaches in traditional design patterns cannot exactly meet the personalized knowledge requirements of designers in cloud environment. To address this issue, we attempt to explore the push strategy of product design knowledge in cloud environment. Firstly, knowledge demands are analyzed with the multidimensional hierarchical context model and the design knowledge modeling is represented following characteristics of the cloud-based design pattern. Then, the knowledge push architecture contains the matching of knowledge to obtain alternative knowledge and the knowledge importance degree prediction with SSA-BPNN model to overcome the inaccuracy of judgments, which is put forward. Moreover, the push coefficient is calculated as the knowledge push reference. Eventually, an illustrative case of intelligent air conditioner product design in the cloud platform is taken to verify the application and performance of the proposed approach. We expect that this work could provide useful insights into the product design knowledge push in cloud environment.     

A collaborative system for capturing and reusing in-context design knowledge with an integrated representation model

Current research on design knowledge capture and reuse has predominantly focused on either the codification view of knowledge or the personalisation view of knowledge, resulting in a failure to address designers’ knowledge needs caused by a lack of context of information and insufficient computational support. Precisely motivated by this gap, this work aims to address the integration of these two views into a complete, contextual and trustworthy knowledge management scheme enabled by the emerging collaborative technologies. Specifically, a knowledge model is developed to represent an integrated knowledge space, which can combine geometric model, knowledge-based analysis codes and problem-solving strategies and processes. On this basis, a smart collaborative system is also designed and developed to streamline the design process as well as to facilitate knowledge capture, retrieval and reuse as users with different roles are working on various tasks within this process. An engineering case study is undertaken to demonstrate the idea of collaborative knowledge creation and sharing and evaluate the effectiveness of the knowledge representation model and the collaborative technologies employed. As evidenced in the development and evaluation, the methods proposed are effective for capturing an integrated knowledge space and the collaborative knowledge management system not only facilitates problem-solving using knowledge-based analysis but also supplies in-context tacit knowledge captured from the communications between users throughout the design process.     

Semantic relation based personalized ranking approach for engineering document retrieval

Since engineering design is heavily informational, engineers want to retrieve existing engineering documents accurately during the product development process. However, engineers have difficulties searching for documents because of low retrieval accuracy. One of the reasons for this is the limitation of existing document ranking approaches, in which relationships between terms in documents are not considered to assess the relevance of the retrieved documents. Therefore, we propose a new ranking approach that provides more correct evaluation of document relevance to a given query. Our approach exploits domain ontology to consider relationships among terms in the relevance scoring process. Based on domain ontology, the semantics of a document are represented by a graph (called Document Semantic Network) and, then, proposed relation-based weighting schemes are used to evaluate the graph to calculate the document relevance score. In our ranking approach, user interests and searching intent are also considered in order to provide personalized services. The experimental results show that the proposed approach outperforms existing ranking approaches. A precisely represented semantics of a document as a graph and multiple relation-based weighting schemes are important factors underlying the notable improvement.     

融入事件实体知识的汉越跨语言新闻事件检索

现有汉越跨语言新闻事件检索方法较少使用新闻领域内的事件实体知识,在候选文档中存在多个事件的情况下,与查询句无关的事件会干扰查询句与候选文档间的匹配精度,影响检索性能。提出一种融入事件实体知识的汉越跨语言新闻事件检索模型。通过查询翻译方法将汉语事件查询句翻译为越南语事件查询句,把跨语言新闻事件检索问题转化为单语新闻事件检索问题。考虑到查询句中只有单个事件,候选文档中多个事件共存会影响查询句和文档的精准匹配,利用事件触发词划分候选文档事件范围,减小文档中与查询无关事件的干扰。在此基础上,利用知识图谱和事件触发词得到事件实体丰富的知识表示,通过查询句与文档事件范围间的交互,提取到事件实体知识表示与词以及事件实体知识表示之间的排序特征。在汉越双语新闻数据集上的实验结果表明,与BM25、Conv-KNRM、ATER等基线模型相比,该模型能够取得较好的跨语言新闻事件检索效果,NDCG和MAP指标最高可提升0.712 2和0.587 2。     

Domain analysis for software reuse

A theory of domain knowledge is proposed that consists of ‘grounded domains' that model a set of cooperating objects that achieve a purpose. Grounded domains have spatial presence in the real world and contain agents that act on objects within a context of structures. More complex meta-domains use grounded domains as their subject matter and describe education, management, etc. The third component of the theory, generic tasks, describes problem solving activity such as diagnosis, searching, planning and scheduling. Generic tasks describe the behavioural components in both grounded and meta-domains. The reusable library of generic models is applied to the design of interactive systems by reusing the models as templates, and to reuse design knowledge in the form of associated design rationale. A process for recognising generic models is described with recognition heuristics structured in a walkthrough type of analysis for identifying key abstractions in new applications. The design process is illustrated with an information retrieval case study developed as a decision support system for emergency management, reusing information searching services. The discussion reviews the prospects for reusable patterns in interactive systems design, and similar approaches in software and knowledge engineering.     

Using iterative refinement to find reusable software

Component libraries are the dominant paradigm for software reuse, but they suffer from a lack of tools that support the problem-solving process of locating relevant components. Most retrieval tools assume that retrieval is a simple matter of matching well-formed queries to a repository. But forming queries can be difficult. A designer's understanding of the problem evolves while searching for a component, and large repositories often use an esoteric vocabulary. CodeFinder is a retrieval system that combines retrieval by reformulation (which supports incremental query construction) and spreading activation (which retrieves items related to the query) to help users find information. I designed it to investigate the hypothesis that this design makes for a more effective retrieval system. My study confirmed that it was more helpful to users seeking relevant information with ill-defined tasks and vocabulary mismatches than other query systems. The study supports the hypothesis that combining techniques effectively satisfies the kind of information needs typically encountered in software design     

QBEES: query-by-example entity search in semantic knowledge graphs based on maximal aspects,diversity-awareness and relaxation

Structured knowledge bases are an increasingly important way for storing and retrieving information. Within such knowledge bases, an important search task is finding similar entities based on one or more example entities. We present QBEES, a novel framework for defining entity similarity based on structural features, so-called aspects and maximal aspects of the entities, that naturally model potential interest profiles of a user submitting an ambiguous query. Our approach based on maximal aspects provides natural diversity awareness and includes query-dependent and query-independent entity ranking components. We present evaluation results with a number of existing entity list completion benchmarks, comparing to several state-of-the-art baselines.     

Fuzzy neural networks for intelligent design retrieval using associative manufacturing features

In the conceptual design stage, designers usually initiate a design concept through an association activity. The activity helps designers collect and retrieve reference information regarding a current design subject instead of starting from scratch. By modifying previous designs, designers can create a new design in a much shorter time. To computerize this process, this paper proposes an intelligent design retrieval system involving soft computing techniques for both feature and object association functions. A feature association method that utilizes fuzzy relation and fuzzy composition is developed to increase the searching spectrum. In the mean time, object association functions composed by a fuzzy neural network allow designers to control the similarity of retrieved designs. Our implementation result shows that the intelligent design retrieval system with two soft computing based association functions can retrieve target reference designs as expected.     

An intelligent approach of knowledge searching within Internet-based distributive knowledge integrated environment

Used to integrate all kinds of knowledge coming from various locations, domains and disciplines, a framework of the Internet-based distributive knowledge integrated system (DKIS) is proposed. Since knowledge repositories are the key components of the DKIS, the efficiency and reliability of the knowledge searching affects the running performance of the DKIS system. We stress methods of efficiently retrieving knowledge from DKIS repositories. Based on artificial neural networks, fuzzy logic and rule reasoning, a novel approach to knowledge searching over the Internet is presented. The issue of knowledge layering is also discussed. Using the rolling bearing as an example, a prototype of knowledge searching is realized. The main aim of this study is to identify an efficient and reliable method of knowledge retrieval for the DKIS within an Internet environment so as to support its perfect operation.     

Effectiveness of keyword-based display and selection of retrieval results for interactive searches

We present an approach to increasing the effectiveness of ranked-output retrieval systems that relies on graphical display and user manipulation of “views” of retrieval results, where a view is the subset of retrieved documents that contain a specified subset of query terms. This approach has been implemented in a system named VIEWER (VIEwing WEb Results), acting as an interface to available search engines. An experimental evaluation of the performance of VIEWER in contrast to AltaVista is the major focus of the paper. We first report the results of an experiment on single, short query searches where VIEWER, used as an interactive ranking system, markedly outperformed AltaVista. We then concentrate on a more realistic searching scenario, involving free query formulation, unconstrained selection of retrieval results, and possibility of query reformulation. We report the results of an experiment where the use of VIEWER, compared to AltaVista, seemed to shift the user effort from inspection to evaluation of results, increasing retrieval effectiveness, and user satisfaction. In particular, we found that the VIEWER users retrieved half as many nonrelevant documents as the AltaVista users while retrieving a comparable number of relevant documents. Published online: 22 September 2000     

An Exploratory Study: Supporting Collaborative Multimedia Systems Design

Multimedia systems design generally requires a collaborative effort from a group of designers with a variety of backgrounds and tasks, such as content experts, instructional designers, media specialists, users, and so forth. However, currently available design tools on the market are mainly designed for a single user. Tools intended to support a collaborative design process should coordinate independent activities of individual designers.This research investigated support for work groups engaged in designing multimedia systems. Specifically, it discussed a new collaborative design environment, called the KMS (Knowledge Management System)-based design environment, in which multimedia designers could share their design knowledge freely. Through two experimental groups, the research investigated impacts of the KMS-based design environment on their collaborative design activities (knowledge creating, knowledge securing, knowledge distributing, and knowledge retrieving activities). The research findings showed that the KMS-based design environment was a promising environment for collaborative multimedia systems design. More specifically, the research findings indicated that the KMS-based design environment supported creating, securing, and retrieving knowledge, but it did not support distributing knowledge. In addition, the research found that the social interactions between group members played important roles in the success of the collaborative multimedia systems design and that the KMS-based design environment did not support the socialization of group members. Furthermore, the research found that the inability of the KMS-based design environment to support the socialization was linked to its low performance level in supporting the knowledge distributing activity. The research explored the desired features of a collaborative support tool for multimedia systems design.     

A RFBSE model for capturing engineers’ useful knowledge and experience during the design process

Reuse of designers’ knowledge and experience of solving problems during the engineering design process holds the key to increase efficiency of decision making in future projects. An important part of this useful knowledge and experience is the interpretation of data and information about design objects and processes as well as the generation of new information for decision-making. However, previous studies on knowledge representation models have mainly focused on developing a structure to describe the knowledge about design objects and design processes while a systematic method that can effectively integrate knowledge about design objects and knowledge about problem-solving strategies is still missing. To fill this gap, a RFBSE knowledge representation model for capturing useful design knowledge and experience for future reuse is developed and evaluated in this study. This paper describes the key elements of this model, explains the rationale of using particular elements, and discusses the evaluation of the model using an engineering design example.     

基于城市安全知识图谱的多关键词流式并行检索算法

我国智慧城市安全概念的普及和建设的逐渐落地,以及大数据在智慧城市安全建设方面的深度应用,对关键词检索的处理响应速度提出了更高的要求。针对这一问题,提出了基于城市安全知识图谱的流式知识图谱多关键词并行检索算法(MKPRASKG),该算法能够根据用户输入的查询关键字,通过关联类图的构建、剪枝和融合操作实时构建基于知识图谱实体的查询子图集,再结合评分函数,以高评分的查询子图为指引,在知识图谱实例数据中进行并行搜索,最终返回Top-k查询结果。实验结果证明,该算法在实时搜索、响应时间、搜索效果以及可扩展性等方面均具有较大的优势。