Papers published on a yearly basis
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08 Nov 2011TL;DR: In this article, a computerized method of predicting customer churn from an organization, including: receiving at a computer server a recorded customer interaction with an agent of the organization, analyzing the received customer interaction to extract basic features that provide an indication regarding the churn probability of the customer; extracting the entity information of the customers from the recorded interaction; retrieving from a database accessible by the server previous interactions for the same entity and extracting advanced features that provided an indication about the churn probabilities of customers.
Abstract: A computerized method of predicting customer churn from an organization, including: receiving at a computer server a recorded customer interaction with an agent of the organization; analyzing the received customer interaction to extract basic features that provide an indication regarding the churn probability of the customer; extracting the entity information of the customer from the recorded interaction; retrieving from a database accessible by the server previous interactions for the same entity and extracting advanced features that provide an indication regarding the churn probability of the customer by comparing multiple interactions of the same entity; predicting a churn probability for the received interaction by applying a statistical customer churn model to the extracted basic features and extracted advanced features; and wherein the interaction and the previous interactions are recordable from more than one type of communication channel by which the customer can communicate with the organization.
24 citations
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23 Dec 2008TL;DR: In this article, an ontology for a domain based on analysis performed on interactions captured in the domain is presented, where concepts belonging to one group are indicated as connected within the ontology.
Abstract: An apparatus and methods for generating an ontology for a domain based on analysis performed on interactions captured in the domain. The analysis provides groups of concepts which are used as topics appearing or retrieved from the interactions are used as topics or concepts in the ontology. Concepts belonging to one group are indicated as connected within the ontology. The ontology can then be used in analyzing further interactions and provide meaning, content and relationships between concepts.
23 citations
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30 Nov 2010TL;DR: In this article, a data provider generates a data encryption key and an identifier, uses the encryption key to encrypt data, sends the encrypted data and the identifier to a data requestor, and sends the data encrypted key and the identifiers to a crypto information server.
Abstract: A data provider generates a data encryption key and an identifier, uses the data encryption key to encrypt data, sends the encrypted data and the identifier to a data requestor, and sends the data encryption key and the identifier to a crypto information server The data requestor sends the identifier to the crypto information server to request the encryption key The crypto information server authenticates the data requestor and, contingent on that authentication, sends the data encryption key to the data requestor If a plurality of data instances are captured, then for each instance, a respective data encryption key and identifier are generated
23 citations
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06 Jul 2009TL;DR: In this article, a method and apparatus for improving speech recognition results for an audio signal captured within an organization, comprising of extracting a phonetic feature and an acoustic feature from the audio signal, decoding the phonetic and acoustic features into phonetic searchable structure, storing both phonetic features in an index, and activating an audio analysis engine which receives the acoustic feature to validate the result and obtain an enhanced result.
Abstract: A method and apparatus for improving speech recognition results for an audio signal captured within an organization, comprising: receiving the audio signal captured by a capturing or logging device; extracting a phonetic feature and an acoustic feature from the audio signal; decoding the phonetic feature into a phonetic searchable structure; storing the phonetic searchable structure and the acoustic feature in an index; performing phonetic search for a word or a phrase in the phonetic searchable structure to obtain a result; activating an audio analysis engine which receives the acoustic feature to validate the result and obtain an enhanced result.
23 citations
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24 Jul 2013TL;DR: A system and method for classifying a webpage may include generating, by an analysis server, a first representation of a webpage and a second representation of the webpage and the method may comprise producing a classification of the web page by relating the first representation to the second representation as mentioned in this paper.
Abstract: A system and method for classifying a webpage may include generating, by an analysis server, a first representation of a webpage. A system and method may include generating, by a unit installed in a user web browser, a second representation of the webpage and the method may comprise producing a classification of the webpage by relating the first representation to the second representation.
23 citations
Authors
Showing all 277 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yaniv Zigel | 21 | 79 | 2170 |
Moshe Wasserblat | 21 | 31 | 1164 |
Oren Pereg | 20 | 31 | 1674 |
J. D. McFall | 19 | 25 | 1862 |
Eyal Kolman | 12 | 38 | 450 |
Moshe Levin | 12 | 28 | 602 |
Yuval Lubowich | 12 | 16 | 529 |
Leon Portman | 11 | 17 | 438 |
Dan Eylon | 11 | 15 | 777 |
Ezra Daya | 10 | 14 | 320 |
Eran Halbraich | 9 | 10 | 290 |
Igal Dvir | 8 | 13 | 902 |
Moshe Wasserblat | 8 | 30 | 491 |
Ronen Laperdon | 8 | 8 | 224 |
Yaniv Gurwicz | 8 | 18 | 215 |