摘要:
Methods and apparatus related to contextual weighting of words. Methods are provided for determining co-occurrence relationships between words in a corpus of word groupings and for contextually weighting words in a word grouping as a function of which other words are present in the word grouping.
摘要:
Given a set of documents relevant to a litigation hold and a seed set of custodians, a second set of custodians can be generated and suggested to a user. After receiving a seed set of keywords and/or custodians, documents are identified based on their relevance. Relevant documents are searched for custodian names, and appropriate custodian names are presented to a user. Additionally, based on a first set of custodians, a suggested set of custodians can be provided to a user based on relationships between the sets of custodians.
摘要:
Given a set of documents relevant to a litigation hold and a seed set of custodians, a second set of custodians can be generated and suggested to a user. After receiving a seed set of keywords and/or custodians, documents are identified based on their relevance. Relevant documents are searched for custodian names, and appropriate custodian names are presented to a user. Additionally, based on a first set of custodians, a suggested set of custodians can be provided to a user based on relationships between the sets of custodians.
摘要:
Given a set of documents relevant to a litigation hold and a seed set of keywords, a second set of keywords can be generated and suggested to a user. Each document in a training set of documents is given an indication of relevance. Based on the indication of relevance, a set of further keywords relevant to the litigation is extracted from the documents and suggested to a user. The suggested set of keywords may or may not include keywords in the seed set. Additionally, the suggested set of keywords may be related to the seed set of keywords.
摘要:
Given a set of documents relevant to a litigation hold and a seed set of keywords, a second set of keywords can be generated and suggested to a user. Each document in a training set of documents is given an indication of relevance. Based on the indication of relevance, a set of further keywords relevant to the litigation is extracted from the documents and suggested to a user. The suggested set of keywords may or may not include keywords in the seed set. Additionally, the suggested set of keywords may be related to the seed set of keywords.
摘要:
An integrated circuit (IC) die has side input/output (IO) pads located along each side of the die interior. Each die corner has a corner IO pad. The side IO pads adjacent to the corner IO pads have shortened passivation regions in the top metal layer (TML) that define TML access regions. TML traces run through the TML access regions to connect the corner IO pads to the die interior. Providing corner IO pads enables an IC die to have up to four more IO pads than a comparable conventional IC die that does not have any corner IO pads, or an IC die to have the same number of IO pads within a smaller overall footprint.
摘要:
An extensible process design provides an ability to dynamically inject changes into a running process instance, such as a BPEL instance. Using a combination of BPEL, rules and events, processes can be designed to allow flexibility in terms of adding new activities, removing or skipping activities and adding dependent activities. These changes do not require redeployment of the orchestration process and can affect the behavior of in-flight process instances. The extensible process design includes a main orchestration process, a set of task execution processes and a set of generic trigger processes. The design also includes a set of rules evaluated during execution of the tasks of the orchestration process. The design can further include three types of events: an initiate process event, a pre-task execution event and a post-task execution event. These events and rules can be used to alter the behavior of the main orchestration process at runtime.
摘要:
The invention, referred to herein as PeaCoCk, uses a unique blend of technologies from statistics, information theory, and graph theory to quantify and discover patterns in relationships between entities, such as products and customers, as evidenced by purchase behavior. In contrast to traditional purchase-frequency based market basket analysis techniques, such as association rules which mostly generate obvious and spurious associations, PeaCoCk employs information-theoretic notions of consistency and similarity, which allows robust statistical analysis of the true, statistically significant, and logical associations between products. Therefore, PeaCoCk lends itself to reliable, robust predictive analytics based on purchase-behavior.
摘要:
A method of modeling includes quantifying a co-operative strength value for a plurality of pairs of variables, and identifying a clique of at least three variables based on a graph of the co-operative strength values of a plurality of pairs of variables. The method also includes selecting a first pair of variables of the plurality of pairs of variables having a high co-operative strength value. A second clique may also be identified. A model of the first clique and a model of the second clique are made. The outputs of these models are combined to form a combined model which is used to make various decisions with respect to real time data.
摘要:
A system for classifying a transaction as fraudulent includes a training component and a scoring component. The training component acts on historical data and also includes a multi-dimensional risk table component comprising one or more multidimensional risk tables each of which approximates an initial risk value for a substantially empty cell in a risk table based upon risk values in cells related to the substantially empty cell. The scoring component produces a score, based in part, on the risk tables associated with groupings of variables having values determined by the training component. The scoring component includes a statistical model that produces an output and wherein the transaction is classified as fraudulent when the output is above a selected threshold value.