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Parallel corpora are important resources in data-driven natural language processing domain. Concerning the issues such as the scale, comprehensiveness and timeliness, the existing Chinese-Mongolian parallel corpora are significantly limited in practical use. Reviewing the traditional heuristic information used to identify major languages parallel web pages, this paper focuses on exploring new heuristic information to improve the performance of identifying Chinese-Mongolian parallel pages. Based on these heuristics, support vector machine is used to classify webs as parallel pages or non-parallel pages. Experiment gains a precision rate of 95% and a recall rate of 88%. This paper makes preliminary research in automatically constructing minority languages parallel corpora from the web.