Crowdsourcing significantly augments the creativity of the public and has become an indispensable component of many problem-solving pipelines. The main challenge, however, is the effective identification of malicious participators while distributing crowdsourcing tasks. In this paper, we propose a novel task-distributing system named Task-Distributing system of crowdsourcing based on Social Relation Cognition (TDSRC) to select qualified participators. First, we divided the tasks into categories according to task themes. Then, we constructed and calculated the Abilities Set (AS), Abilities Values (AVs), and the Friends’ Abilities Matrix (FAM) by using the historical interactive texts between a given task publisher (requester) and its friends. When a requester distributes a task, TDSRC can generate the candidate participators’ sequence based on the task needs and FAM. Finally, the best-matched friends in the sequence are selected as the task receivers (solvers), thus producing a personal FAM to disseminate the tasks. The experimental results indicate that (1) the proposed system can accurately and effectively discover the requester’s friends’ abilities and select appropriate solvers and (2) the natural trust relationship in the social network reduces fraudsters and enhances the quality of crowdsourcing services.

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utilize high technology to boost the fast development of the national economy. Since the project of agricultural science and technology to farmer was put into practice by Ministry of Agriculture in 2005, 212 representative counties have been set, 200,000 typical households have been added, and 4 million peasants have enhanced production and increased income. According to the criterion of Software Engineering, the article collected the information of Agricultural science and technology to farmer and the geography information of all villages and towns in HUA county, designed the system structure of Agricultural distribution by tools of OOP, GIS components and network database, integrating GIS and MIS smoothly. The system has been applied in HUA county, and facilitated information management, analysis and decision-making to the agricultural science and technology to farmer.With the rapid progress of information technology, more and more people management, and realized the special topic analysis to the information science and technology to farmer, implemented the information query and

In this paper, we propose a robust approach about color image retrieval. It can realize fast matching in CBIR (Content-Based Image Retrieval) when we search in large image databases. Indexes root in object features of Z image which is the result of re-quantization in HSV color space, matching with a non-geometrical distance is based on objects, so time consumption pixel by pixel can be avoided. Because Z image is made up of many color clustering regions and invariant moments are used for feature representation, our approach is robust to translation, scale and rotation.