Abstract: Comparative decision systems and methods are disclosed for gathering and mining data representative of purchase decisions. One disclosed comparative decision system detects when a user is comparing items and provides the user with the ability to create a research note storing comparative information for the alternative items. The system displays information about items according to a variety of factors. The user can customize the factors and enter information for each alternative item according to the various factors. Some information may be pre-populated by the system. The research note may be made visible to other users, and may be suggested to another user based on the note's expected helpfulness and relevance to that user. One disclosed method for mining data stored within research notes identifies which factors are given higher relative priorities by users considering a purchase. Another mining method analyzes the effects of price changes on item popularity.

Abstract: Techniques are described for assessing information supplied by users in various ways, such as to assess the reliability and/or other attributes of the user-supplied information. In at least some situations, the user-supplied information includes votes or other evaluations supplied by users related to items available from an online merchant, such as ratings of usefulness or other attributes of item reviews for the items or of other types of content pieces that are provided by other users. If user-supplied information is assessed as being sufficiently reliable and/or to have other desired attributes of interest, such as based on an automated analysis of the information, the user-supplied information may be used in various ways in various embodiments, such as to rate the quality or other attributes of the evaluated content pieces, and/or to rate quality or other attributes of the content-providing users who provide the content pieces.

Abstract: This disclosure is directed to measuring test effects using adjusted outlier data. Test data and control data may include some outlier data (i.e., right-side tails of distribution curves), which may bias the resultant data. The outlier data may be adjusted to reduce bias. A cutoff point is selected along the distribution of data. Data below the cutoff is maintained and used to determine an effect of the data below the cutoff point. The effect of the data above the cutoff may be processed as follows. Predictor data is identified from the data below, but near, the cutoff point. The predictor data may then be used determine the effect of the outlier data that is above the cutoff point. In some embodiments, the predictor data may be weighted and combined with a weighted portion of the outlier data to determine an effect of the data above the cutoff point.

Abstract: Comparative decision systems and methods are disclosed for gathering and mining data representative of purchase decisions. One disclosed comparative decision system detects when a user is comparing items and provides the user with the ability to create a research note storing comparative information for the alternative items. The system displays information about items according to a variety of factors. The user can customize the factors and enter information for each alternative item according to the various factors. Some information may be pre-populated by the system. The research note may be made visible to other users, and may be suggested to another user based on the note's expected helpfulness and relevance to that user. One disclosed method for mining data stored within research notes identifies which factors are given higher relative priorities by users considering a purchase. Another mining method analyzes the effects of price changes on item popularity.

Abstract: Comparative decision systems and methods are disclosed for gathering and mining data representative of purchase decisions. One disclosed comparative decision system detects when a user is comparing items and provides the user with the ability to create a research note storing comparative information for the alternative items. The system displays information about items according to a variety of factors. The user can customize the factors and enter information for each alternative item according to the various factors. Some information may be pre-populated by the system. The research note may be made visible to other users, and may be suggested to another user based on the note's expected helpfulness and relevance to that user. One disclosed method for mining data stored within research notes identifies which factors are given higher relative priorities by users considering a purchase. Another mining method analyzes the effects of price changes on item popularity.

Abstract: Comparative decision systems and methods are disclosed for gathering and mining data representative of purchase decisions. One disclosed comparative decision system detects when a user is comparing items and provides the user with the ability to create a research note storing comparative information for the alternative items. The system displays information about items according to a variety of factors. The user can customize the factors and enter information for each alternative item according to the various factors. Some information may be pre-populated by the system. The research note may be made visible to other users, and may be suggested to another user based on the note's expected helpfulness and relevance to that user. One disclosed method for mining data stored within research notes identifies which factors are given higher relative priorities by users considering a purchase. Another mining method analyzes the effects of price changes on item popularity.

Abstract: Comparative decision systems and methods are disclosed for gathering and mining data representative of purchase decisions. One disclosed comparative decision system detects when a user is comparing items and provides the user with the ability to create a research note storing comparative information for the alternative items. The system displays information about items according to a variety of factors. The user can customize the factors and enter information for each alternative item according to the various factors. Some information may be pre-populated by the system. The research note may be made visible to other users, and may be suggested to another user based on the note's expected helpfulness and relevance to that user. One disclosed method for mining data stored within research notes identifies which factors are given higher relative priorities by users considering a purchase. Another mining method analyzes the effects of price changes on item popularity.

Abstract: Techniques are described for assessing users who provide content, such as based on the provided content and/or on aspects of how/when the content is provided. In at least some situations, the users being assessed are author users who create some or all of the content that they provide, while in other situations users may provide other types of content (e.g., content that is identified and/or selected by the users, but not created by the users). Assessment of the content-providing users may be performed in various manners, such as to generate one or more user contribution scores or other user contribution ratings for some or all such users, such as to reflect a combination of multiple factors (e.g., a quantity of pieces of content provided by a user, a recency of providing some or all of the content pieces, an assessed quality of the provided content pieces, etc.).