Abstract: A combination five gallon bucket opener, includes a handle portion and a head portion, a first opener feature located in the head portion, the first opener feature having a plurality of engaging members and a bearing surface, at least one of the engaging members configured to receive a tab of a lid, at least one of the engaging members configured to engage a top surface of the lid, and a second opener feature located in the head portion, the second opener feature having at least one extended member configured to receive a cap, the at least one extended member having at least one feature defined therein to engage a corresponding feature on the cap.

Abstract: Technologies are described herein for the facilitation of authorized in-store pickup in conjunction with online ordering. A request to process an order of an item selected by a customer and placed through a website may be received. The website may be transformed to a cart fulfillment web page including a fulfillment interface. Through the fulfillment interface, a selection of an option for in-store pickup by a third party may be received from the customer. Through the fulfillment interface, identifying information regarding the third party, pickup details associated with the in-store pickup of the item by the third party, and a preferred notification method for contacting the third party may also be received from the customer. An authorization pickup record related to the in-store pickup of the item by the third party may be generated. The authorization pickup record may be transmitted to the third party via the preferred notification method.

Abstract: This application includes embodiments of apparatuses (e.g., bath benches) for improving accessibility to a bathtub. Some embodiments include a bath bench with a primary deck and a folding lateral transfer extension (secondary deck). The secondary deck may be coupled to the primary deck by a dual-axis hinge.

Abstract: Price for one or more products is optimized by considering competitor and/or consumer behavior relating to the products. A control set is generated to include one or more products. Also, a test set is generated to include one or more products of the same type as products in the control set. A feature of the products in the test set is changed while the feature of the products in the control set is maintained. Competitor and/or consumer response to the change is measured. Based on the response, a recommendation is generated with respect to the feature of the products in the test set. According to one implementation the recommendation may be a recommendation to lower the price of the products in the test set.

Abstract: Information from a plurality of domains is automatically extracted according to an iterative application of rules. A first rule is generated based on a target string. The first rule comprises at least one filter. A domain of interest is identified and a training set is generated using the target string and at least one document in the domain of interest. The first rule is applied to each document in the training set to obtain a first of target results. The first set of target results are compared to desired set of target results. Based on the comparison, a second rule may is created and applied to the training set to yield an improved second set of target results.

Abstract: A source product and a competitor product are automatically matched by computing similarity scores between the products. An attribute of a source product is extracted from information received from a user. The extracted attribute is then used to generate a search term. A search for competitor product information is performed using the search term and a similarity score between the source product and the competitor product is calculated. In one implementation, the similarity score is calculated by generating a first value pair for the source product and the competitor product, and for the first value pair, (1) assigning a value to a degree of similarity between the source product and the competitor product with respect to a common feature, and (2) finding the product of the assigned value and a weight value assigned to the common feature.

Abstract: A product assortment system includes a crawler obtaining product information from one or more domains and storing the product information in a database. A user interface determines one or more product categories associated with one or more products of a customer. A keyword module determines criteria for associating one or more products of one or more competitors with the product categories. The user interface generates a display indicating overlap of the one or more products of the customer with the one or more products of the competitors.

Abstract: Price alerts relating to competitor products are transmitted to a user. A user provides product information, which is used to generate a product set. The products in the product set are used to generate a competitor set, which includes competitors that offer products in the product set. A rule set is generated that includes rules applied to the products and the competitors. A search is performed for the products against the competitors to determine if a rule has been broken. If so, an alert is transmitted to the user. In some implementations, instructions are also transmitted to correct the broken rule. Steps to correct the broken rule may include lowering the price offered by the user for the product.

Abstract: Competitors are classified in terms of products the competitors offer. A product set is generated from product information received from a user. Also, a competitor set is generated, where the competitor set comprises at least one competitor determined to be relevant to one or more products in the product set. A target price rule is generated that is operative to change a price offered by the user for the at least one product. A competitors relevancy can be determined by considering factors such as: (1) unique visitors to the competitor's website, (2) reviews on the competitor's website (3), ratings on the competitor's website, (4) absolute number of products common to the user's website and the competitor's website, (5) percentage number of products common to the user's website and the competitor's website, and (6) number of products offered by the competitor that comprise the product set.

Abstract: Wrappers are induced for multiple domains where, for a given target string having relatively universal distribution across domains of interest, a first wrapper may be defined and trained for a particular domain. Target strings extracted from that domain may be used to search for documents in other domains. New wrappers may be learned for other domains also containing the target strings. Further, a first wrapper may be learned for a given domain using a limited amount of training data from that single domain. The first wrapper is then applied to all pages in the domain to extract the relevant information. A few of the new words extracted are then searched against the document collection to obtain a list of domains that contain the extracted words. The updated information may be used as training data to learn new wrappers on those domains.