Abstract: A variety of techniques are described by which keyword sets and target audience profiles may be generalized in a systematic and effective way with reference to relationships between keywords, profiles, and the data of an underlying user population.

Abstract: A system and method to facilitate automatic categorization of events in a network, wherein one or more keywords are retrieved from a keyword database, each retrieved keyword matching a corresponding event unit of an event input by a user over a network. A dominant keyword corresponding to a highest parameter value calculated for each retrieved keyword is then selected. Finally, the event is categorized based on one or more categories associated with the dominant keyword. The dominant keyword may be selected based on one or more keyword categories associated with each retrieved keyword and an ambiguity parameter value calculated for each keyword. Alternatively, the dominant keyword may be selected based on a highest-ranked output value calculated for each retrieved keyword. One or more categories associated with the dominant keyword are subsequently retrieved from the keyword database and the event is categorized based on the category associated with the dominant keyword.

Abstract: In a computerized search system, a document corpus is searched according to a query and results of the search are presentable as an ordered search result set comprising one or more search hits, a search hit being a document of the document corpus or reference thereto. Based on content of the search result set, a number of suggested queries and/or parameter options are presented to a querier, thereby allowing the querier to select a suggested query and/or provide values for the parameters and those selections can be used to reorder the hits of the search result set. The particular suggested queries and/or parameters presented depend on the page elements of the search result set's documents and their categorization. The categorization might be done using concept networks.

Abstract: Techniques are provided for reranking and increasing the relevance of the results Internet searches. A search query is initially parsed into individual units. Each unit corresponds to one or more words that represents a natural concept. A concept network is analyzed to locate concepts that are related to the units in the search query. Particular concepts are selected from the concept network. Independent Internet searches are performed for each of the selected concepts. The search results from these searches are then compared to units in the original search query and ranked according to their relevance to the original search query.

Abstract: Multiple concept networks are generated from subsets of received queries. These concept networks can be used in various ways to enhance response to subsequent queries. In one embodiment, concept networks can be merged into a larger concept network that can be used to infer a user's likely intent given a query. In another embodiment, suggestions for related searches obtained using different concept networks can be merged or aggregated. Other users for concept networks in query processing, including assisted search, are also described.

Abstract: Systems and methods for processing search requests are provided, including automatic generation of taxonomies and query processing using those taxonomies.

Abstract: Search results are processed using search requests, including analyzing received queries in order to provide a more sophisticated understanding of the information being sought. A concept network is generated from a set of queries by parsing the queries into units and defining various relationships between the units. From these concept networks, queries can be automatically categorized into categories, or more generally, can be associated with one or more nodes of a taxonomy. The categorization can be used to alter the search results or the presentation of the results to the user. As an example of alterations of search results or presentation, the presentation might include a list of “suggestions” for related search query terms. As other examples, the corpus searched might vary depending on the category or the ordering or selection of the results to present to the user might vary depending on the category.

Abstract: In a search processing system, a concept network is generated from a set of queries by parsing the queries into units and defining various relationships between the units based in part on patterns of units that appear together in queries. Units in the concept network that have some similar characteristic(s) are grouped into superunits. For each superunit, there is a corresponding signature that defines the similar characteristic of the group. A query is processed by identifying constituent units, determining the superunit membership of some or all of the constituent units, and using that information to formulate a response to the query.