Question-Answering Pair Matching Based on Question Classification and Ensemble Sentence Embedding

Question-answering(QA)models find answers to a given question.The necessity of automatically finding answers is increasing because it is very important and challenging from the large-scale QA data sets.In this paper,we deal with the QA pair matching approach in QA models,which finds the most relevant question and its recommended answer for a given question.Existing studies for the approach performed on the entire dataset or datasets within a category that the question writer manually specifies.In contrast,we aim to automatically find the category to which the question belongs by employing the text classification model and to find the answer corresponding to the question within the category.Due to the text classification model,we can effectively reduce the search space for finding the answers to a given question.Therefore,the proposed model improves the accuracy of the QA matching model and significantly reduces the model inference time.Furthermore,to improve the performance of finding similar sentences in each category,we present an ensemble embedding model for sentences,improving the performance compared to the individual embedding models.Using real-world QA data sets,we evaluate the performance of the proposed QA matching model.As a result,the accuracy of our final ensemble embedding model based on the text classification model is 81.18%,which outperforms the existing models by 9.81%∼14.16%point.Moreover,in terms of the model inference speed,our model is faster than the existing models by 2.61∼5.07 times due to the effective reduction of search spaces by the text classification model.

Optimizing Bidders Selection of Multi-Round Procurement Problem in Software Project Management Using Parallel Max-Min Ant System Algorithm

This paper presents a Game-theoretic optimization via Parallel Min-Max Ant System(PMMAS)algorithm is used in practice to determine the Nash equilibrium value to resolve the confusion in choosing appropriate bidders of multi-round procurement problem in software project management.To this end,we introduce an approach that proposes:(i)A Game-theoretic model of multiround procurement problem(ii)A Nash equilibrium strategy corresponds to multi-round strategy bid(iii)An application of PSO for the determination of global Nash equilibrium.The balance point in Nash Equilibrium can help to maintain a sustainable structure not only in terms of project management but also in terms of future cooperation.As an alternative of procuring entities subjectively,a methodology to support decision making has been studied using Nash equilibrium to create a balance point on benefit in procurement where buyers and suppliers need multiple rounds of bidding.Our goal focus on the balance point in Nash Equilibrium to optimizing bidder selection in multi-round procurement which is the most beneficial for both investors and selected tenderers.Our PMMAS algorithm is implemented based on MPI(message passing interface)to find the approximate optimal solution for the question of how to choose bidders and ensure a path for a win-win relationship of all participants in the procurement process.We also evaluate the speedup ratio and parallel efficiency between our algorithm and other proposed algorithms.As the experiment results,the high feasibility and effectiveness of the PMMAS algorithm are verified.

Chinese Question-Answering System

Traditional Chinese text retrieval systems return a ranked list of documentsin response to a user''s request. While a ranked list of documents may be an appropriate response forthe user, frequently it is not. Usually it would be better for the system to provide the answeritself instead of requiring the user to search for the answer in a set of documents. Since Chinesetext retrieval has just been developed lately, and due to various specific characteristics ofChinese language, the approaches to its retrieval are quite different from those studies andresearches proposed to deal with Western language. Thus, an architecture that augments existingsearch engines is developed to support Chinese natural language question answering. In this paper anew approach to building Chinese question-answering system is described, which is thegeneral-purpose, fully-automated Chinese quest ion-answering system available on the web. In theapproach, we attempt to represent Chinese text by its characteristics, and try to convert theChinese text into ERE (E: entity, R: relation) relation data lists, and then to answer the questionthrough ERE relation model. The system performs quite well giving the simplicity of the techniquesbeing utilized. Experimental results show that question-answering accuracy can be greatly improvedby analyzing more and more matching ERE relation data lists. Simple ERE relation data extractiontechniques work well in our system making it efficient to use with many backend retrieval engines.

Ecological impact assessment method of highways in Tibetan Plateau:A Case study of Gonghe-Yushu Expressway

In recent years,the ecological environment along highways in Tibetan Plateau has been severely affected due to the rapid construction of highways.In order to solve the problems of multiple indicators and inconsistent criteria in the ecological impact assessment of highways,and to scientifically screen assessment indicators,the paper proposes a multi-round indicator screening method,which combines literature analysis,expert rating,and statistical analysis.Based on this screening method,normalized difference vegetation index,land surface temperature,elevation,and normalized difference soil index are screened out.Combined with multiple linear regression,an ecological impact assessment model is established and applied to ecological impact assessment of Gonghe-Yushu Expressway.The results show that the expressway construction is the first driving force for the deterioration of the ecological environment along the roadside,and its interference range on the desert grassland ecosystem is greater than that on the agroforestry system.The ecological environment within 150 m on both sides of the expressway should be protected.

Multi-robot task allocation for exploration

The problem of allocating a number of exploration tasks to a team of mobile robots in dynamic environments was studied. The team mission is to visit several distributed targets. The path cost of target is proportional to the distance that a robot has to move to visit the target. The team objective is to minimize the average path cost of target over all targets. Finding an optimal allocation is strongly NP-hard. The proposed algorithm can produce a near-optimal solution to it. The allocation can be cast in terms of a multi-round single-item auction by which robots bid on targets. In each auction round, one target is assigned to a robot that produces the lowest path cost of the target. The allocated targets form a forest where each tree corresponds a robot’s exploring targets set. Each robot constructs an exploring path through depth-first search in its target tree. The time complexity of the proposed algorithm is polynomial. Simulation experiments show that the allocating method is valid.

Using LSA and text segmentation to improve automatic Chinese dialogue text summarization

Automatic Chinese text summarization for dialogue style is a relatively new research area. In this paper, Latent Semantic Analysis （LSA） is first used to extract semantic knowledge from a given document, all question paragraphs are identified, an automatic text segmentation approach analogous to Text＇filing is exploited to improve the precision of correlating question paragraphs and answer paragraphs, and finally some ＂important＂ sentences are extracted from the generic content and the question-answer pairs to generate a complete summary. Experimental results showed that our approach is highly efficient and improves significantly the coherence of the summary while not compromising informativeness.

Question-answering system based on concepts and statistics

Question-answering systems provide short answers with the use of available information.The implementation mechanism for a question answering system is presented in this paper and is based on concepts and statistics.The system determines the question and focuses on the answer types,making different conceptual expansions for different questions.It applies the latent semantic indexing(LSI)method to retrieve relevant passages.It uses matching algorithms to find a match between questions and sentences stored in a database.It also extracts answers from a frequently asked questions(FAQ)database by finding matching or similar sentences.The answering ability of the system has been improved with the use of LSI and FAQ.The question-answering system introduced in Chinese universities is a developed and proven system capable of precise results.

Domain-Specific Formal Ontology of Archaeology and Its Application in Knowledge Acquisition and Analysis

Inherent heterogeneity and distribution of knowledge strongly prevent knowledge from sharing and reusing among different agents and software entities, and a formal ontology has been viewed as a promising means to tackle this problem. In this paper, a domain-specific formal ontology of archaeology is presented. The ontology mainly consists of three parts: archaeological categories, their relationships and axioms. The ontology not only captures the semantics of archaeological knowledge, but also provides archaeology with an explicit and formal specification of a shared conceptualization, thus making archaeological knowledge shareable and reusable across humans and machines in a structured fashion. Further, we propose a method to verify ontology. correctness based on the individuals of categories. As applications of the ontology,we have developed an ontology-driven approach to knowledge acquisition from archaeological text and a question answering system for archaeological knowledge.

Promoting Student Participation in Seminar Courses:A Case Study

Using a conversation analysis approach, the present study investigates the teacher-led question-answer sequences of one successful seminar course （Short Stories and Western Culture） within the curriculum reform for English majors in Beijing Foreign Studies University, aiming at uncovering an effective way of integrating disciplinary learning with language skills development. The result of the analysis shows that the teacher of the course, who perceives student participation as an indispensable ingredient of his class, often uses more divergent, opinion-seeking questions to initiate discussion and uses four types of expansion question on his turns to promote student participation, namely, probing questions （PQ）, clue-giving questions （CQ）, elaboration requests （ER）, and agreement checks （AC）. The study also generates an I-R-（E）-F-FC [Initiation-Response-（Evaluation）-FoUow up-Further Contribution] model, in which the teacher attempts to promote student participation and guide the construction of students＇ understanding.