Abstract: Text processing includes: segmenting received text based on a lexicon of smallest semantic units to obtain medium-grained segmentation results; merging the medium-grained segmentation results to obtain coarse-grained segmentation results, the coarse-grained segmentation results having coarser granularity than the medium-grained segmentation results; looking up in the lexicon of smallest semantic units respective search elements that correspond to segments in the medium-grained segmentation results; and forming fine-grained segmentation results based on the respective search elements, the fine-grained segmentation results having finer granularity than the medium-grained segmentation results.

Abstract: The present disclosure discloses a method for generating a search result and an information search system. The method for generating a search result includes: receiving, by an information search system, a search request; obtaining, by searching, a plurality of pieces of matching information that match the search request; obtaining a respective amount of user response associated with each of the plurality of pieces of matching information and further obtaining a total amount of user response associated with a respective categories to which each of the plurality of pieces of matching information belongs; and ranking the plurality of pieces of information to generate a search result based on the total amount of user response associated with the respective category to which each of the plurality of pieces of matching information belongs.

Abstract: A method of expressing auxin synthetase gene specifically in cotton seed coat and fiber, which comprises constructing plant expression vector capable of expressing auxin synthetase gene specifically by fusing a tissue-specific promoter with an auxin synthetase gene, and then integrating the construct into a cotton genome. The method can significantly improve the yield and the quality of cotton fiber, thereby providing fiber with high quality for textile industry.

Abstract: The present disclosure describes a search method, a search apparatus and a search system. The method includes: a data rewriting system that obtains, from a database, one or more search term candidates that are relevant to a present search term. The data rewriting system retrieves properties of the present search term and the one or more search term candidates, where the properties describe respective matching results of the present search term and the one or more search term candidates. Based on the matching results, the data rewriting system determines whether or not the present search term needs to be rewritten, and rewrites the present search term based on the matching results to provide a rewritten present search term if it is determined that the present search term needs to be rewritten. A search engine performs a search based on the rewritten present search term.

Abstract: The present disclosure provides a method and apparatus of knowledge base building to automatically construct a knowledge base. Furthermore, the disclosed techniques can be used to improve the accuracy of that knowledge base. In one aspect, a method acquires a sentence from a webpage using a basic data processing layer of a computing apparatus. The acquired sentence is parsed into words using a data mining layer of the computing apparatus. One or more representative words in a first category of a knowledge base are matched with the words parsed from the acquired sentence. When there is a match between one of the representative words and one of the words parsed from the acquired sentence, a string of words adjacent the matched word in the acquired sentence is added to the first category as a first entry.

Abstract: An information retrieval method includes pre-processing a set of historical query information and processing a user query. Pre-processing a set of historical query information includes determining a plurality of semantic patterns based on a plurality of queries in the set of historical query information; establishing correspondence relationships between the plurality of semantic patterns and a plurality of filtering and ranking operations. Processing a user query comprises receiving the user query; retrieve a plurality of results in response to the user query; determining a semantic pattern that corresponds to the user query; determining a set of filtering and ranking operations that corresponds to the semantic pattern based on the correspondence relationships; and performing the set of filtering and ranking operations on the plurality of results to generate a set of filtered and ranked results.

Abstract: A method and an apparatus for identifying synonym and utilizing such synonym to conduct search is disclosed. The disclosed method includes: obtaining arbitrary two words to be identified; determining whether a shortest edit distance between the two words less than or equal to an edit distance threshold; determining whether the two words to be identified exist in a preset knowledge database, and if an answer is yes then searching a smallest granularity type with highest weight value for each word in the knowledge database; and if the two word have the same smallest granularity type with highest weight value, then determining such two words are synonyms, or non-synonym otherwise. The disclosed techniques greatly improve accuracy of synonym identification and guarantee effect of synonym identification.

Abstract: Ranking search results, comprises receiving a query string; retrieving a plurality of search results that include a corresponding plurality of target strings that relate to the query string; segmenting the query string and each of the plurality of target strings; pairing segments in the query string with respective segments in the target strings to form a plurality of combinations; retrieving a plurality of weights that correspond to the plurality of combinations based on a mapping of word combinations and their respective weights, wherein a weight measures semantic correlation between words in a word combination; and determining a weighted word length based on the weights corresponding to each of the plurality of target strings; and ranking the plurality of target strings based on their respective weighted word lengths.

Abstract: Generating ranked search results includes receiving a plurality of matching information items that match a search request, ranking at least some of the plurality of matching information items using a linear ranking model that linearly combines a first plurality of feature values to obtain a first set of ranked results, ranking at least some of the first set of ranked results using a nonlinear ranking model that nonlinearly combines a second plurality of feature values to obtain a second set of ranked results, and provide a search response based on the second set of ranked results.

Abstract: Sampling analysis includes classifying a plurality of query keywords into a plurality of query keyword subsets according to page view (PV) values associated with the plurality of query keywords, the plurality of query keywords being submitted by a plurality of users; determining a respective plurality of sample rates of a respective plurality of query keywords in a respective one of the plurality of query keyword subsets; and sampling query data in the respective one of the plurality of query keyword subsets according to the respective plurality of sample rates.