職稱英語考試的大多數題型都是閱讀理解，下面是小編整理的.職稱英語概括大意與理解句子的真題，歡迎大家閱讀!
下面的短文後有2項測試任務：(1)第23~26題要求從所給的6個選項中為第2～5段每段選擇1個最佳標題;(2)第27～30題要求從所給的6個選項中為每個句子確定1個最佳選項。
First Image-recognition Software1. Dartmouth researchers and their colleagues have created an artificial intelligence software that uses photos to locate documents on the Internet with far greater accuracy than ever before.
2. The new system, which was tested on photos and is now being applied to videos, shows for the first time that a machine learning algorithm (運算法則) for image recognition and retrieval is accurate and efficient enough to improve large-scale document searches online. The system uses pixel (畫素) data in images and potentially video — rather than just text — to locate documents. It learns to recognize the pixels associated with a search phrase by studying the results from text-based image search engines. The knowledge gleaned (收集) from those results can then be applied to other photos without tags or captions (圖片說明), making for more accurate document search results.
3. "Over the last 30 years," says Associate Professor Lorenzo Torresani, a co-author of the study, "the Web has evolved from a small collection of mostly text documents to a modern, massive, fast-growing multimedia data set, where nearly every page includes multiple pictures or videos. When a person looks at a Web page, he immediately gets the gist (主旨) of it by looking at the pictures in it. Yet, surprisingly, all existing popular search engines, such as Google or Bing, strip away the information contained in the photos and use exclusively the text of Web pages to perform the document retrieval. Our study is the first to show that modern machine vision systems are accurate and efficient enough to make effective use of the information contained in image pixels to improve document search."
4. The researchers designed and tested a machine vision system — a type of artificial intelligence that allows computers to learn without being explicitly programmed — that extracts semantic (語義的) information from the pixels of photos in Web pages. This information is used to enrich the description of the HTML page used by search engines for document retrieval. The researchers tested their approach using more than 600 search queries (查詢)on a database of 50 million Web pages. They selected the text-retrieval search engine with the best performance and modified it to make use of the additional semantic information extracted by their method from the pictures of the Web pages. They found that this produced a 30 percent improvement in precision over the original search engine purely based on text.
23. Paragraph 1 ____
24. Paragraph 2 ____
25. Paragraph 3 ____
26. Paragraph 4 ____
A. Function of the new system
B. Improvement in document retrieval
C. Publication of the new discovery
D. Problems of the existing search engines
E. Popularity of the new system
F. Artificial intelligence software created
27. The new system does document retrieval by ____.
28. The new system is expected to improve precision in ____.
29. When performing document retrieval the existing search engines ignore __ __
30. The new system was found more effective in document search than the ____
A. using photos
B. description of the HTML page
C. current popular search engines
D. document search
E. information in images
F. machine vision systems
First Image-recognitions software1) Dartmouth researchers and their colleagues have created an artificial intelligence software that uses photos to locate documents on the Internet with far greater accuracy than ever before.
2)The new system, which was tested on photos and is now being applied to videos, shows for the first time that a machine learning algorithm(運演算法則)for image recognition and retrieval is accurate and efficient enough to improve large-scale document searches online. The system uses pixel(畫素)data in images and potentially video—rather than just text—to locate documents. It learns to recognize the pixels associated with a search phrase by studying the results from text-based image search engines. The knowledge gleaned(收集)from those results can then be applied to other photos without tags or captions(圖片說明),making for more accurate document search results.
3)“Over the last 30 years,” says Associate Professor Korenzo Torresani, a co-author of the study,” the web has evolved from a small collection of mostly text documents to a modern, massive, fast-growing multimedia datastet, where nearly every page includes multiple pictures of videos. When a person looks at a Web page, he immediately get the gist(主旨)of it by looking at the pictures in it. Yet, surprisingly, all existing popular search engine, such as Google or Bing, strip away the information contained in the photos and use exclusively the text of Wed pages to perform the document retrieval. Our study is the first to show that modern machine vision systems are accurate and efficient enough to make effective use of the information contained in image pixels to improve document search.”
4)The researchers designed and tested a machine vision system—a type of artificialintelligence that allows computers to learn without being explicitly programmed— that extracts semantic(語義的)information from pixels of photos in Web pages. This informationg is used to enrich the description of the HTML page used by search engines for document retrieval. The researchers tested their approach using more than 600 search queries(查詢)on a database of 50 million Wed pages. They selected the text-retrieval search engine with the best performance and modified it to make use of the additional semantic information extracted by their method from the pictures of the Web pages. They found tht this produced a 30 percent improvement in precision over the original search engine purely based on text.
23. Paragraph 1 _____
24. Paragraph 2 _____
25. Paragraph 3 _____
26 Paragraph 4 _____
A. Popularity of the new system
B. Publication of the new discovery
C tion of the new system
D. Artificial intelligence software created
E. Problems of the existing search engines
F ovement in document retrieval
