Abstract: Embodiments of the present invention provide electronic devices, information processing methods and computer programs products wherein collecting units are used for collecting images. A display unit can be used for displaying images collected by the collecting unit on a first plane. A collecting support can be used for installing the collecting unit, wherein the collecting support comprises: a first movable support, arranged on the case of the display unit through a first rotating shaft, which can rotate in a second plane perpendicular to the first plane; a second movable support, arranged on the first movable support through a second rotating shaft, which can rotate relative to the first movable support in the second plane; and wherein the collecting unit is arranged on the second movable support.

Abstract: Various users' navigational behaviors relative to search results presented by a search engine are monitored. URLs that are visited and revised queries that are submitted after the submission of an original query are placed within a trail that begins with the original query. These trails are grouped based on the original queries with which they begin. For each trail group, a set of URLs that frequently occur in that group's trails, and a set of revised queries that frequently occur in that group's trails, are determined. These frequently occurring elements are mapped to the original queries with which all the trails in the corresponding trail group begin. In response to subsequent submissions of the same original query, the search engine ensures that URLs and revised queries that are mapped to the original query are prominently displayed on the search results pages that are initially returned in response to those submissions.

Abstract: Approaches and techniques are discussed for ranking the documents indicated in search results for a query based on click-through information collected for the query in previous query sessions. According to an embodiment of the invention, when calculating a relevance score for a particular document, one may overcome positional bias by utilizing click-through information about other documents previously returned in the same search results as the particular document. According to an embodiment, one may utilize Dynamic Bayesian Network, based on said click-through information, to model relevance. According to an embodiment of the invention, one may utilize click-through information to generate targets for learning a ranking function.

Abstract: According to an example embodiment, a method comprises executing instructions by a special purpose computing apparatus to, for labeled source domain data having a plurality of original labels, generate a plurality of first predicted labels for the labeled source domain data using a target function, the target function determined by using a plurality of labels from labeled target domain data. The method further comprises executing instructions by the special purpose computing apparatus to apply a label relation function to the first predicted labels for the source domain data and the original labels for the source domain data to determine a plurality of weighting factors for the labeled source domain data.

Abstract: Various users' navigational behaviors relative to search results presented by a search engine are monitored. URLs that are visited and revised queries that are submitted after the submission of an original query are placed within a trail that begins with the original query. These trails are grouped based on the original queries with which they begin. For each trail group, a set of URLs that frequently occur in that group's trails, and a set of revised queries that frequently occur in that group's trails, are determined. These frequently occurring elements are mapped to the original queries with which all the trails in the corresponding trail group begin. In response to subsequent submissions of the same original query, the search engine ensures that URLs and revised queries that are mapped to the original query are prominently displayed on the search results pages that are initially returned in response to those submissions.

Abstract: A system for determining the intent of query that includes a search engine that receives a first search query, a query/click log module configured to store log data associated with the first search query; and a computational module that generates metric values associated with the first search query based on the log data and that determines that the first search query is one of a regional specific query or a global query based on the metric values, where the metric values reflect a likelihood of local intent of the first search query, and where the search engine provides search results selected in part based on the metric values.

Abstract: According to an example embodiment, a method comprises executing instructions by a special purpose computing apparatus to, for labeled source domain data having a plurality of original labels, generate a plurality of first predicted labels for the labeled source domain data using a target function, the target function determined by using a plurality of labels from labeled target domain data. The method further comprises executing instructions by the special purpose computing apparatus to apply a label relation function to the first predicted labels for the source domain data and the original labels for the source domain data to determine a plurality of weighting factors for the labeled source domain data.

Abstract: Approaches and techniques are discussed for ranking the documents indicated in search results for a query based on click-through information collected for the query in previous query sessions. According to an embodiment of the invention, when calculating a relevance score for a particular document, one may overcome positional bias by utilizing click-through information about other documents previously returned in the same search results as the particular document. According to an embodiment, one may utilize Dynamic Bayesian Network, based on said click-through information, to model relevance. According to an embodiment of the invention, one may utilize click-through information to generate targets for learning a ranking function.

Abstract: The present invention relates to systems and methods for determining a content item relevance function. The method comprises collecting user preference data at a search provider for storage in a user preference data store and collecting expert-judgment data at the search provider for storage in an expert sample data store. A modeling module trains a base model through the use of the expert-judgment data and tunes the base model through the use of the user preference data to learn a set of one or more tuned models. A measure (B measure) is designed to evaluate the balanced performance of tuned model over expert judgment and user preference. The modeling module generates or selects the content item relevance function from the tuned models with B measure as the selection criterion.

Abstract: A system for determining the intent of query that includes a search engine that receives a first search query, a query/click log module configured to store log data associated with the first search query; and a computational module that generates metric values associated with the first search query based on the log data and that determines that the first search query is one of a regional specific query or a global query based on the metric values, where the metric values reflect a likelihood of local intent of the first search query, and where the search engine provides search results selected in part based on the metric values.

Abstract: The present invention relates to systems and methods for determining a content item relevance function. The method comprises collecting user preference data at a search provider for storage in a user preference data store and collecting expert-judgment data at the search provider for storage in an expert sample data store. A modeling module trains a base model through the use of the expert-judgment data and tunes the base model through the use of the user preference data to learn a set of one or more tuned models. A measure (B measure) is designed to evaluate the balanced performance of tuned model over expert judgment and user preference. The modeling module generates or selects the content item relevance function from the tuned models with B measure as the selection criterion.

Abstract: Mesophilic methane bacteria obtained from digested sludge are acclimatized in an H2/CO2 medium and the acclimatized methane bacteria are grown on a support inclusive of inorganic nutritional salts of trace metal elements by using an immobilized bed bioreactor. The grown bacteria are allowed to metabolize a mixed gas, prepared by adding hydrogen to at least one of coal gas and biogas, into methane and at the same time, cobalamin contained in the fermented liquor is recovered as an extracellular product in the form of cyanocobalamin by using potassium cyanide to thereby produce vitamin B12 efficiently in a high content and high yield.

Abstract: Mesophilic methane bacteria obtained from digested sludge are acclimatized in an H2/CO2 medium and the acclimatized methane bacteria are grown on a support inclusive of inorganic nutritional salts of trace metal elements by using an immobilized bed bioreactor. The grown bacteria are allowed to metabolize a mixed gas, prepared by adding hydrogen to at least one of coal gas and biogas, into methane and at the same time, cobalamin contained in the fermented liquor is recovered as an extracellular product in the form of cyanocobalamin by using potassium cyanide to thereby produce vitamin B12 efficiently in a high content and high yield.

Abstract: Mesophilic methane bacteria obtained from digested sludge are acclimatized in an H2/CO2 medium and the acclimatized methane bacteria are grown on a support inclusive of inorganic nutritional salts of trace metal elements by using an immobilized bed bioreactor. The grown bacteria are allowed to metabolize a mixed gas, prepared by adding hydrogen to at least one of coal gas and biogas, into methane and at the same time, cobalamin contained in the fermented liquor is recovered as an extracellular product in the form of cyanocobalamin by using potassium cyanide to thereby produce vitamin B12 efficiently in a high content and high yield.