How do you design and conduct bilingual text summarization experiments and evaluations?

2 Define your summarization methods

The next step is to define your summarization methods for bilingual text summarization. You need to decide whether you want to use extractive methods, which select sentences or phrases from the original texts, or abstractive methods, which generate new sentences or phrases based on the original texts. You also need to decide whether you want to use monolingual methods, which summarize each text separately, or multilingual methods, which summarize texts jointly or cross-lingually. Monolingual methods are simpler and faster, but multilingual methods are more coherent and consistent.

3 Set your evaluation metrics

The third step is to set your evaluation metrics for bilingual text summarization. You need to measure the quality, relevance, and readability of the summaries in different languages. You also need to compare the summaries with human references or baselines. You can use automatic metrics, such as ROUGE, BLEU, or METEOR, which compare the summaries with references based on n-gram overlap, or manual metrics, such as content, fluency, or adequacy, which ask human judges to rate the summaries based on criteria. Automatic metrics are cheaper and scalable, but manual metrics are more reliable and comprehensive.

4 Design your experimental setup

The fourth step is to design your experimental setup for bilingual text summarization. You need to specify the parameters, settings, and configurations of your data sources, summarization methods, and evaluation metrics. You also need to ensure the validity, reliability, and reproducibility of your experiments. You can use standard frameworks, such as DUC, TAC, or MultiLing, which provide common data sets, tasks, and guidelines for text summarization, or custom frameworks, which allow you to adapt your experiments to your specific needs and goals.

5 Conduct your experiments and analyses

The fifth step is to conduct your experiments and analyses for bilingual text summarization. You need to run your summarization methods on your data sources and evaluate the summaries with your evaluation metrics. You also need to analyze the results and identify the strengths, weaknesses, and challenges of your methods. You can use statistical tests, such as t-test, ANOVA, or Wilcoxon, which compare the differences between the methods based on significance levels, or qualitative analyses, such as error analysis, case studies, or user feedback, which examine the reasons and implications behind the results.

6 Report your findings and contributions

The final step is to report your findings and contributions for bilingual text summarization. You need to present your experimental setup, results, and analyses in a clear, concise, and coherent way. You also need to discuss the limitations, implications, and future directions of your research. You can use academic formats, such as papers, posters, or presentations, which follow the conventions and standards of your field, or popular formats, such as blogs, podcasts, or videos, which reach a wider and more diverse audience.